library(tidyverse)
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In system("timedatectl", intern = TRUE) :
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# library(MouseGastrulationData)
library(SingleCellExperiment)
library(scater)
library(scran)
library(bit64)
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library(patchwork)
library(ggpubr)
source('~/milo/notebooks/benchmark/benchmark_utils.R')
figdir <- "~/mount/gdrive/milo/Figures/benchmark_v2/"
if (!dir.exists(figdir)) {
dir.create(figdir)
}
cannot create dir '/home/jovyan/mount/gdrive/milo/Figures/benchmark_v2', reason 'No such file or directory'
Some plotting utils
## color palette for methods
method_names <- c("milo", "daseq", "meld", "louvain", "cydar")
method_colors <- RColorBrewer::brewer.pal(7, name="Dark2")[c(1:4,6)]
method_colors <- setNames(method_colors, method_names)
method_labels <- c("Milo", "DAseq", "MELD", "Louvain", "cydar")
method_labels <- setNames(method_labels, method_names)
scale_color_methods <- function(){ scale_color_manual(values = method_colors, labels=method_labels) }
scale_fill_methods <- function(){ scale_fill_manual(values = method_colors, labels=method_labels) }
data.frame(method_names) %>%
ggplot(aes(method_names, 2, color=method_names )) + geom_point(size=5) +
scale_color_methods()
enr_labeller2 <- function(value){
fc <- round(prob2FC(as.numeric(value)), 2)
enr_name <- paste("logFC = ", fc)
return(c(value=enr_name))
}
pl_labeller <- labeller(method=as_labeller(setNames(method_labels, method_names)),
enr=enr_labeller2)
In this notebook I will visualize the results from benchmarking Milo against 4 alternative DA analysis methods.
All the main functions are implemented in benchmark/benchmark_utils.R. These functions are wrapped in several scripts:
make_bm_data.R (wrapped in submit_make_bm_data.sh)run_DA_R.rrun_meld.pysubmit_benchmark.sh (contains parameters for each input dataset)These are going to be used as underlying KNN graphs with different topologies for benchmarking.
Provided by Mike, constructed with dyntoy
Prepare datasets (uniform naming of dim reduction and celltype column)
branch_sce_3x <- readRDS("~/mount/gdrive/milo/BranchingSimulation-3X.RDS")
branch_sce_3x$cell <- colnames(branch_sce_3x)
branch_sce_3x$celltype <- branch_sce_3x$group_id
names(reducedDims(branch_sce_3x)) <- c("pca.corrected", "UMAP")
saveRDS(branch_sce_3x, "/nfs/team205/ed6/data/milo_benchmark/branching3x_data_bm.RDS")
linear_sce_3x <- readRDS("~/mount/gdrive/milo/LinearTrajSyntheticLabels-3X.RDS")
linear_sce_3x$cell <- colnames(linear_sce_3x)
linear_sce_3x$celltype <- linear_sce_3x$group_id
names(reducedDims(linear_sce_3x)) <- c("pca.corrected", "UMAP")
saveRDS(linear_sce_3x, "/nfs/team205/ed6/data/milo_benchmark/linear3x_data_bm.RDS")
cluster_sce_3x <- readRDS("~/mount/gdrive/milo/DiscreteSyntheticLabels-3X.RDS")
cluster_sce_3x$cell <- colnames(cluster_sce_3x)
cluster_sce_3x$celltype <- cluster_sce_3x$Block
names(reducedDims(cluster_sce_3x)) <- c("pca.corrected", "UMAP")
saveRDS(cluster_sce_3x, "/nfs/team205/ed6/data/milo_benchmark/cluster3x_data_bm.RDS")
Select samples from late time points (even number of replicates)
AtlasSampleMetadata %>%
arrange(stage) %>%
mutate(sample=factor(sample, levels=unique(sample))) %>%
ggplot(aes(stage, sample)) +
geom_point()
late_samples <- AtlasSampleMetadata %>%
filter(stage %in% c("E7.75", "E8.0", "E8.25", "E8.5")) %>%
pull(sample)
embryo_sce <- EmbryoAtlasData(type="processed", samples = late_samples)
data.frame(colData(embryo_sce)) %>%
ggplot(aes(as.factor(sample), as.factor(pool))) + geom_point()
embryo_sce
Preprocessing
logcounts(embryo_sce) <- log1p(counts(embryo_sce))
## Exclude zero counts genes
keep.rows <- rowSums(logcounts(embryo_sce)) != 0
embryo_sce <- embryo_sce[keep.rows, ]
dec <- modelGeneVar(embryo_sce)
hvgs <- getTopHVGs(dec, n=5000)
## Drop cells with NAs in corrected pca (low quality)
embryo_sce <- embryo_sce[,apply(reducedDim(embryo_sce, "pca.corrected"), 1, function(x) all(!is.na(x)))]
## Run UMAP (the data has been subsetted)
# embryo_sce <- scater::runPCA(embryo_sce, subset_row=hvgs)
embryo_sce <- scater::runUMAP(embryo_sce, dimred="pca.corrected")
plotReducedDim(embryo_sce, "UMAP", colour_by="celltype", text_by="celltype", point_size=0.1) +
scale_color_manual(values=EmbryoCelltypeColours) +
guides(color=guide_legend(override.aes = list(size=2)))
Save object 4 benchmark
saveRDS(embryo_sce, "/nfs/team205/ed6/data/milo_benchmark/embryo_data_bm.RDS")
embryo_sce <- readRDS("/nfs/team205/ed6/data/milo_benchmark/embryo_data_bm.RDS")
Save list of celltype names and sample by sizes
for (i in 1:3) {
pop_size_df <- as.data.frame(table(embryo_sce$celltype)) %>%
rename(pop=Var1, pop_size=Freq) %>%
mutate(size_bin = cut(pop_size, breaks = 10)) %>%
group_by(size_bin) %>%
sample_n(size=1)
write(as.character(pop_size_df$pop), glue("/nfs/team205/ed6/data/milo_benchmark/pop_sample_{i}.txt"))
}
Sanity check of synthetic labels on embryo data
pops <- scan("/nfs/team205/ed6/data/milo_benchmark/pop_sample_2_clean.txt", what="")
umap_ls <- lapply(pops, function(p){
filename <- paste0('/nfs/team205/ed6/data/milo_benchmark/synthetic_data/benchmark_embryo_pop_',
str_replace(p, " ", "_"),
'_enr0.8_seed45.coldata.csv')
if (file.exists(filename)){
coldata <- read_csv(filename)
colData(embryo_sce) <- column_to_rownames(coldata) %>% DataFrame()
data.frame(reducedDim(embryo_sce, 'UMAP')) %>%
dplyr::rename(UMAP1=X1, UMAP2=X2) %>%
mutate(Condition1_prob=embryo_sce$Condition1_prob > 0.6) %>%
ggplot(aes(UMAP1, UMAP2, color=Condition1_prob)) +
ggrastr::geom_point_rast(size=0.1, dpi=700) +
scale_color_viridis_d() +
theme_classic(base_size = 16)
}
})
umap_ls
pops <- scan("/nfs/team205/ed6/data/milo_benchmark/pop_sample_2_clean.txt", what="")
umap_ls <- lapply(pops, function(p){
filename <- paste0('/nfs/team205/ed6/data/milo_benchmark/synthetic_data/benchmark_embryo_pop_',
str_replace(p, " ", "_"),
'_enr0.9_seed45.coldata.csv')
if (file.exists(filename)){
coldata <- read_csv(filename)
colData(embryo_sce) <- column_to_rownames(coldata) %>% DataFrame()
data.frame(reducedDim(embryo_sce, 'UMAP')) %>%
dplyr::rename(UMAP1=X1, UMAP2=X2) %>%
mutate(Condition1_prob=embryo_sce$Condition1_prob > 0.6) %>%
ggplot(aes(UMAP1, UMAP2, color=Condition1_prob)) +
ggrastr::geom_point_rast(size=0.1, dpi=700) +
scale_color_viridis_d() +
theme_classic(base_size = 16)
}
})
umap_ls
Read full outcomes and true probabilities
read4_prob_hist <- function(data_id){
outdir <- glue("/nfs/team205/ed6/data/milo_benchmark/{data_id}/")
res_files <- list.files(outdir, pattern=glue("{data_id}.+batchEffect0.DAresults"))
res_files_full <- list.files(outdir, pattern=glue("{data_id}.+batchEffect0.DAresults"), full.names = TRUE)
res_files_full_nomeld <- str_subset(res_files_full, "meld|cydar_batch|louvain_batch|milo_batch", negate = TRUE)
res_ls <- lapply(seq_along(res_files_full_nomeld), function(i){
print(paste("Outcome no. ", i))
benchmark_df <- read_csv(res_files_full_nomeld[i])
## Check if conditions were swapped in test
pred_cor <- benchmark_df %>%
mutate(pred=factor(pred, levels=c("NegLFC", "NotDA", "PosLFC"), ordered = TRUE)) %>%
mutate(pred=as.numeric(pred)) %>%
summarise(cor(pred, true_prob))
## Swap outcomes if so
if (!is.na(pred_cor)) {
if (pred_cor < - 0.1) {
benchmark_df <- mutate(benchmark_df, pred = ifelse(pred=="NegLFC", "PosLFC", ifelse(pred=="PosLFC", "NegLFC", "NotDA")))
}
}
benchmark_df
})
res_df <- res_ls %>%
purrr::reduce(bind_rows) %>%
select(true_prob, pred, method)
return(res_df)
}
cluster_res_df <- read4_prob_hist("cluster3x")
linear_res_df <- read4_prob_hist("linear3x")
branch_res_df <- read4_prob_hist("branching3x")
embryo_res_df <- read4_prob_hist("embryo")
Plot distribution of P(C1) in cells identified as DA by different methods
calculate_quantile_thresh <- function(res_df){
return(quantile(1-res_df[res_df$method=="milo",][["true_prob"]], probs = seq(0,1, by=0.25))["75%"])
}
plot_p_hist <- function(res_df){
## Calculate threshold
thresh <- calculate_quantile_thresh(res_df)
## Plot histogram of p(C1) for predicted DA cells
p <- res_df %>%
dplyr::filter(pred!="NotDA") %>%
# mutate(color=ifelse(true_prob==0.5, "0.5","0")) %>%
ggplot(aes(1 - true_prob)) +
# geom_density(aes(color=pred)) +
facet_grid(method~pred, scales="free_y", labeller=pl_labeller) +
geom_histogram(bins=50, aes(fill=pred)) +
xlab("P(C1)") + ylab("# DA cells") +
theme_bw(base_size=16) +
scale_fill_brewer(palette="Set1", name="Predicted effect") +
geom_vline(xintercept = thresh, linetype=2)
p
}
# plot_p_hist(cluster_res_df) + ggtitle("clusters")
plot_p_hist(linear_res_df) + ggtitle("linear") +
plot_p_hist(branch_res_df) + ggtitle("branching") +
plot_p_hist(embryo_res_df) + ggtitle("embryo") +
plot_layout(guides="collect") +
ggsave(paste0(figdir, "/pC1_histograms.pdf"), width=18, height = 6)
Use 75% quantile of P(C1) in all cells to define threshold for true DA
linear_thresh <- calculate_quantile_thresh(linear_res_df)
Warning messages:
1: In readChar(file, size, TRUE) : truncating string with embedded nuls
2: In readChar(file, size, TRUE) : truncating string with embedded nuls
branching_thresh <- calculate_quantile_thresh(branch_res_df)
embryo_thresh <- calculate_quantile_thresh(embryo_res_df)
Define utils
## Util to compute benchmark outcome given a probability threshold for true DA
Warning message:
In system("timedatectl", intern = TRUE) :
running command 'timedatectl' had status 1
.outcome_by_prob <- function(benchmark_df, da_upper){
DA_thresh <- 1 - da_upper
benchmark_df <- benchmark_df %>%
mutate(true = ifelse(benchmark_df$true_prob < DA_thresh, "NegLFC", ifelse(benchmark_df$true_prob > 1-DA_thresh, "PosLFC", "NotDA")))
if (benchmark_df$method[1]=="meld") {
benchmark_df <- mutate(benchmark_df, pred = ifelse(Condition2 < DA_thresh, "NegLFC", "NotDA"))
}
## Check if conditions were swapped in test
pred_cor <- benchmark_df %>%
group_by(pred) %>%
summarise(m=mean(true_prob)) %>%
ungroup() %>%
mutate(pred=factor(pred, levels=c("NegLFC", "NotDA", "PosLFC"), ordered = TRUE)) %>%
mutate(pred=as.numeric(pred)) %>%
summarise(c=cor(pred, m)) %>%
pull(c)
## Swap outcomes if so
if (!is.na(pred_cor)) {
if (pred_cor < 0) {
benchmark_df <- mutate(benchmark_df, pred = ifelse(pred=="NegLFC", "PosLFC", ifelse(pred=="PosLFC", "NegLFC", "NotDA")))
}
}
calculate_outcome(benchmark_df)
}
## Util to plot benchmarking results on UMAP
plot_outcome_umap <- function(sce, method, pop, enr, seed, batchEffect, true=FALSE, data_id="embryo",
red_dim="umap_batch",
rasterize=FALSE){
coldata_file <- list.files(indir, pattern=paste0(".+",data_id,"_pop_", pop,"_enr",enr,"_seed", seed, ".coldata.csv"),
full.names = TRUE)
colData(sce) <- read_csv(coldata_file) %>% column_to_rownames() %>% DataFrame()
res_file <- list.files(outdir,
pattern= paste0(".+",data_id,"_pop_", pop,"_enr",enr,"_seed", seed, '.+batchEffect',batchEffect,".DAresults.",method,".csv"),
full.names = TRUE)
if (method=="meld") {
sce$predicted <- ifelse(read_csv(res_file)[["Condition2"]] < 0.3, "NegLFC", 'NotDA')
} else if (method=="daseq") {
sce$predicted <- ifelse(read_csv(res_file)[["pred"]] == "NegLFC", 'PosLFC', ifelse(read_csv(res_file)[["pred"]] == "PosLFC", "NegLFC", "NotDA"))
} else {
sce$predicted <- read_csv(res_file)[["pred"]]
}
if (true) {
pl <- data.frame(reducedDim(sce, red_dim)) %>%
dplyr::rename(UMAP1=X1, UMAP2=X2) %>%
mutate(true=sce$Condition1_prob) %>%
arrange(true) %>%
ggplot(aes(UMAP1, UMAP2, color=true)) +
geom_point(size=0.1) +
scale_color_viridis_c(name="C1 probability", limits=c(0.5,0.9)) +
theme_classic(base_size=18) +
guides(color=guide_colorbar(title.position="top", title.hjust = 0.5)) +
theme(axis.ticks = element_blank(),
axis.text = element_blank(),
legend.position = "top") +
xlab("UMAP1") + ylab("UMAP2")
} else {
pl <- data.frame(reducedDim(sce, red_dim)) %>%
dplyr::rename(UMAP1=X1, UMAP2=X2) %>%
dplyr::mutate(method=method) %>%
dplyr::mutate(predicted=factor(sce$predicted, levels=c("NegLFC", "PosLFC", 'NotDA'))) %>%
dplyr::arrange(- predicted) %>%
ggplot(aes(UMAP1, UMAP2, color=predicted)) +
geom_point(size=0.1) +
geom_point(data= . %>% filter(predicted!="NotDA"), size=0.2) +
scale_color_manual(values=c(NegLFC="red", NotDA="grey", PosLFC="blue"),
labels=c(NegLFC="Enriched in C1", NotDA="No DA", PosLFC="Depleted in C1"), name='') +
guides(color = guide_legend(override.aes = list(size=1))) +
theme_classic(base_size=18) +
theme(legend.position=c(.15,.2), axis.ticks = element_blank(),
axis.text = element_blank()) +
xlab("UMAP1") + ylab("UMAP2") +
facet_wrap(method~.)
}
if (rasterize) {
pl <- pl + rasterize(geom_point(size=0.1), dpi = 300)
}
pl
}
## Convert condition probability to LFC
prob2FC <- function(prob){
log((prob)/(1 - prob))
}
outdir <- "/nfs/team205/ed6/data/milo_benchmark/linear3x/"
res_files <- list.files(outdir, pattern="linear.+DAresults")
res_files_full <- list.files(outdir, pattern="linear3x.+DAresults", full.names = TRUE)
in_files <- list.files("~/data/milo_benchmark/synthetic_data/", pattern="linear3x.+coldata.csv")
## Make data frame w benchmark parameters
linear_out_meta_df <- data.frame(file_id = str_remove_all(res_files, "benchmark_embryo_pop_|.csv")) %>%
separate(col = file_id, sep = ".DAresults.", into=c("file_id", "method")) %>%
separate(col = file_id, sep = "_enr", into=c("pop", "file_id")) %>%
separate(col = file_id, sep = "_", into=c("enr", "seed", "batchEffect")) %>%
mutate(seed=str_remove(seed, "seed"), batchEffect=str_remove(batchEffect, "batchEffect"))
## Load results
linear_outcome_df <- lapply(seq_along(res_files_full), function(i){
print(paste("Outcome no. ", i))
benchmark_df <- read_csv(res_files_full[i]) %>%
.outcome_by_prob(da_upper = linear_thresh) %>%
mutate(DA_thresh=linear_thresh) %>%
ungroup() %>%
dplyr::select(- method) %>%
bind_cols(linear_out_meta_df[i,])
pop_enr <- as.numeric(linear_out_meta_df[i,"enr"])
benchmark_df
}) %>%
purrr::reduce(bind_rows) %>%
## Remove MELD
filter(method!="meld")
linear_outcome_df
pl_df <- linear_outcome_df %>%
filter(method!="milo_batch") %>%
mutate(FDR = FP/(TP+FP)) %>%
mutate(TPR=ifelse(is.nan(TPR), 0, TPR),
FPR=ifelse(is.nan(FPR), 0, FPR),
FDR=ifelse(is.nan(FDR), 0, FDR),
Precision=ifelse(is.nan(Precision), 0, Precision)) %>%
mutate(pop=str_replace(pop, "_", " ")) %>%
mutate(pop=factor(pop, levels=unique(pop))) %>%
filter(DA_thresh >= linear_thresh & batchEffect==0)
pl_right <- pl_df %>%
ggplot(aes(as.factor(round(prob2FC(as.numeric(enr)),1)), TPR, color=method)) +
geom_boxplot(outlier.alpha = 0) +
ggbeeswarm::geom_quasirandom(alpha=0.5, position="stack", size=0.5) +
theme_bw(base_size = 16) +
scale_color_manual(values = method_colors, labels=setNames(method_labels, method_names)) +
scale_fill_manual(values = method_colors, labels=setNames(method_labels, method_names)) +
facet_grid(.~method, labeller=pl_labeller) +
theme(#axis.text.x = element_blank(), axis.ticks.x = element_blank(),
axis.title.x = element_blank())
pl_left <- pl_df %>%
ggplot(aes(as.factor(round(prob2FC(as.numeric(enr)),1)), FDR, color=method)) +
geom_boxplot(outlier.alpha = 0) +
ggbeeswarm::geom_quasirandom(alpha=0.5, position="stack", size=0.5) +
geom_hline(yintercept = 0.1, linetype=2) +
theme_bw(base_size = 16) +
scale_color_manual(values = method_colors, labels=setNames(method_labels, method_names)) +
scale_fill_manual(values = method_colors, labels=setNames(method_labels, method_names)) +
facet_grid(.~method, labeller=pl_labeller) +
theme(#axis.text.x = element_blank(), axis.ticks.x = element_blank(),
axis.title.x = element_blank())
pl <- pl_right / pl_left +
plot_layout(guides='collect') &
theme(#axis.text.x = element_blank(), axis.ticks.x = element_blank(),
axis.title.x = element_blank())
pl
Plot UMAP
linear_sce <- readRDS("~/data/milo_benchmark/linear3x_data_bm.RDS")
indir <- "~/data/milo_benchmark/synthetic_data/"
names(reducedDims(linear_sce))[2] <- "umap_batch"
colnames(reducedDims(linear_sce)[[2]]) <- c("X1", "X2")
pl_top <- plot_outcome_umap(linear_sce, method = 'milo', pop="M5", enr = 0.9, seed = 43,batchEffect = 0, true = TRUE, data_id="linear3x") +
theme(legend.position="top")
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
rowname = [31mcol_character()[39m,
group_id = [31mcol_character()[39m,
cell = [31mcol_character()[39m,
celltype = [31mcol_character()[39m,
synth_labels = [31mcol_character()[39m,
synth_samples = [31mcol_character()[39m,
synth_batches = [31mcol_character()[39m,
Condition1_prob = [32mcol_double()[39m,
Condition2_prob = [32mcol_double()[39m,
true_labels = [31mcol_character()[39m
)
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
plot_linear <- ((pl_top) | (pl & theme(legend.position="top"))) +
plot_layout(widths = c(0.5,2))
plot_linear
outdir <- "/nfs/team205/ed6/data/milo_benchmark/branching3x/"
res_files <- list.files(outdir, pattern="branching3x.+DAresults")
res_files_full <- list.files(outdir, pattern="branching3x.+DAresults", full.names = TRUE)
in_files <- list.files("~/data/milo_benchmark/synthetic_data/", pattern="branching3x.+coldata.csv")
## Make data frame w benchmark parameters
branch_out_meta_df <- data.frame(file_id = str_remove_all(res_files, "benchmark_embryo_pop_|.csv")) %>%
separate(col = file_id, sep = ".DAresults.", into=c("file_id", "method")) %>%
separate(col = file_id, sep = "_enr", into=c("pop", "file_id")) %>%
separate(col = file_id, sep = "_", into=c("enr", "seed", "batchEffect")) %>%
mutate(seed=str_remove(seed, "seed"), batchEffect=str_remove(batchEffect, "batchEffect"))
## Load results
branch_outcome_df <- lapply(seq_along(res_files_full), function(i){
print(paste("Outcome no. ", i))
benchmark_df <- read_csv(res_files_full[i]) %>%
.outcome_by_prob(da_upper = branching_thresh) %>%
mutate(DA_thresh=branching_thresh) %>%
ungroup() %>%
dplyr::select(- method) %>%
bind_cols(branch_out_meta_df[i,])
pop_enr <- as.numeric(branch_out_meta_df[i,"enr"])
benchmark_df
}) %>%
purrr::reduce(bind_rows) %>%
## Remove MELD
filter(method!="meld")
branch_outcome_df
pl_df <- branch_outcome_df %>%
filter(method!="milo_batch") %>%
mutate(FDR = FP/(TP+FP)) %>%
mutate(TPR=ifelse(is.nan(TPR), 0, TPR),
FPR=ifelse(is.nan(FPR), 0, FPR),
FDR=ifelse(is.nan(FDR), 0, FDR),
Precision=ifelse(is.nan(Precision), 0, Precision)) %>%
mutate(pop=str_replace(pop, "_", " ")) %>%
mutate(pop=factor(pop, levels=unique(pop))) %>%
filter(DA_thresh >= branching_thresh & batchEffect==0)
pl_right <- pl_df %>%
ggplot(aes(as.factor(round(prob2FC(as.numeric(enr)),1)), TPR, color=method)) +
geom_boxplot(outlier.alpha = 0) +
ggbeeswarm::geom_quasirandom(alpha=0.5, position="stack", size=0.5) +
theme_bw(base_size = 16) +
scale_color_manual(values = method_colors, labels=setNames(method_labels, method_names)) +
scale_fill_manual(values = method_colors, labels=setNames(method_labels, method_names)) +
facet_grid(.~method, labeller=pl_labeller) +
theme(#axis.text.x = element_blank(), axis.ticks.x = element_blank(),
axis.title.x = element_blank())
pl_left <- pl_df %>%
ggplot(aes(as.factor(round(prob2FC(as.numeric(enr)),1)), FDR, color=method)) +
geom_boxplot(outlier.alpha = 0) +
ggbeeswarm::geom_quasirandom(alpha=0.5, position="stack", size=0.5) +
geom_hline(yintercept = 0.1, linetype=2) +
theme_bw(base_size = 16) +
scale_color_manual(values = method_colors, labels=setNames(method_labels, method_names)) +
scale_fill_manual(values = method_colors, labels=setNames(method_labels, method_names)) +
facet_grid(.~method, labeller=pl_labeller) +
theme(#axis.text.x = element_blank(), axis.ticks.x = element_blank(),
axis.title.x = element_blank())
pl <- pl_right / pl_left +
plot_layout(guides='collect') &
theme(#axis.text.x = element_blank(), axis.ticks.x = element_blank(),
axis.title.x = element_blank())
pl
Plot UMAP
branch_sce <- readRDS("~/data/milo_benchmark/branching3x_data_bm.RDS")
indir <- "~/data/milo_benchmark/synthetic_data/"
names(reducedDims(branch_sce))[2] <- "umap_batch"
colnames(reducedDims(branch_sce)[[2]]) <- c("X1", "X2")
pl_top <- plot_outcome_umap(branch_sce, method = 'milo', pop="M5", enr = 0.9, seed = 43,batchEffect = 0, true = TRUE, data_id="branching3x") +
theme(legend.position="top")
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
rowname = [31mcol_character()[39m,
group_id = [31mcol_character()[39m,
cell = [31mcol_character()[39m,
celltype = [31mcol_character()[39m,
synth_labels = [31mcol_character()[39m,
synth_samples = [31mcol_character()[39m,
synth_batches = [31mcol_character()[39m,
Condition1_prob = [32mcol_double()[39m,
Condition2_prob = [32mcol_double()[39m,
true_labels = [31mcol_character()[39m
)
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
plot_branch <- ((pl_top) | (pl & theme(legend.position="top"))) +
plot_layout(widths = c(0.5,2))
plot_branch
outdir <- "/nfs/team205/ed6/data/milo_benchmark/cluster3x/"
res_files <- list.files(outdir, pattern="cluster3x.+DAresults")
res_files_full <- list.files(outdir, pattern="cluster3x.+DAresults", full.names = TRUE)
in_files <- list.files("~/data/milo_benchmark/synthetic_data/", pattern="cluster3x.+coldata.csv")
## Make data frame w benchmark parameters
cluster_out_meta_df <- data.frame(file_id = str_remove_all(res_files, "benchmark_embryo_pop_|.csv")) %>%
separate(col = file_id, sep = ".DAresults.", into=c("file_id", "method")) %>%
separate(col = file_id, sep = "_enr", into=c("pop", "file_id")) %>%
separate(col = file_id, sep = "_", into=c("enr", "seed", "batchEffect")) %>%
mutate(seed=str_remove(seed, "seed"), batchEffect=str_remove(batchEffect, "batchEffect"))
## Load results
cluster_outcome_df <- lapply(seq_along(res_files_full), function(i){
print(paste("Outcome no. ", i))
benchmark_df <- read_csv(res_files_full[i]) %>%
.outcome_by_prob(da_upper = 0.55) %>%
mutate(DA_thresh=0.55) %>%
ungroup() %>%
dplyr::select(- method) %>%
bind_cols(cluster_out_meta_df[i,])
pop_enr <- as.numeric(cluster_out_meta_df[i,"enr"])
benchmark_df
}) %>%
purrr::reduce(bind_rows) %>%
## Remove MELD
filter(method!="meld")
[1] "Outcome no. 1"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 2"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 3"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 4"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
rowname = [31mcol_character()[39m,
Condition2 = [32mcol_double()[39m,
method = [31mcol_character()[39m,
true = [31mcol_character()[39m,
true_prob = [32mcol_double()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 5"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 6"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 7"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 8"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 9"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
rowname = [31mcol_character()[39m,
Condition2 = [32mcol_double()[39m,
method = [31mcol_character()[39m,
true = [31mcol_character()[39m,
true_prob = [32mcol_double()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 10"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 11"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 12"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 13"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 14"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
rowname = [31mcol_character()[39m,
Condition2 = [32mcol_double()[39m,
method = [31mcol_character()[39m,
true = [31mcol_character()[39m,
true_prob = [32mcol_double()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 15"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 16"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 17"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 18"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 19"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 20"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 21"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 22"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 23"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 24"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 25"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 26"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 27"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 28"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 29"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 30"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 31"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
rowname = [31mcol_character()[39m,
Condition2 = [32mcol_double()[39m,
method = [31mcol_character()[39m,
true = [31mcol_character()[39m,
true_prob = [32mcol_double()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 32"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 33"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 34"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 35"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 36"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
rowname = [31mcol_character()[39m,
Condition2 = [32mcol_double()[39m,
method = [31mcol_character()[39m,
true = [31mcol_character()[39m,
true_prob = [32mcol_double()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 37"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 38"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 39"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 40"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 41"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
rowname = [31mcol_character()[39m,
Condition2 = [32mcol_double()[39m,
method = [31mcol_character()[39m,
true = [31mcol_character()[39m,
true_prob = [32mcol_double()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 42"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 43"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 44"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 45"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 46"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 47"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 48"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 49"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 50"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 51"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 52"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 53"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 54"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 55"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 56"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 57"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 58"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
rowname = [31mcol_character()[39m,
Condition2 = [32mcol_double()[39m,
method = [31mcol_character()[39m,
true = [31mcol_character()[39m,
true_prob = [32mcol_double()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 59"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 60"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 61"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 62"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 63"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
rowname = [31mcol_character()[39m,
Condition2 = [32mcol_double()[39m,
method = [31mcol_character()[39m,
true = [31mcol_character()[39m,
true_prob = [32mcol_double()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 64"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 65"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 66"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 67"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 68"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
rowname = [31mcol_character()[39m,
Condition2 = [32mcol_double()[39m,
method = [31mcol_character()[39m,
true = [31mcol_character()[39m,
true_prob = [32mcol_double()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 69"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 70"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 71"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 72"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 73"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 74"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 75"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 76"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 77"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 78"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 79"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 80"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 81"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 82"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 83"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 84"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 85"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
rowname = [31mcol_character()[39m,
Condition2 = [32mcol_double()[39m,
method = [31mcol_character()[39m,
true = [31mcol_character()[39m,
true_prob = [32mcol_double()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 86"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 87"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 88"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 89"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 90"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
rowname = [31mcol_character()[39m,
Condition2 = [32mcol_double()[39m,
method = [31mcol_character()[39m,
true = [31mcol_character()[39m,
true_prob = [32mcol_double()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 91"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 92"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 93"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 94"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 95"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
rowname = [31mcol_character()[39m,
Condition2 = [32mcol_double()[39m,
method = [31mcol_character()[39m,
true = [31mcol_character()[39m,
true_prob = [32mcol_double()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 96"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 97"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 98"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 99"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 100"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 101"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 102"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 103"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 104"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 105"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 106"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 107"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 108"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 109"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 110"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 111"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 112"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
rowname = [31mcol_character()[39m,
Condition2 = [32mcol_double()[39m,
method = [31mcol_character()[39m,
true = [31mcol_character()[39m,
true_prob = [32mcol_double()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 113"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 114"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 115"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 116"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 117"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
rowname = [31mcol_character()[39m,
Condition2 = [32mcol_double()[39m,
method = [31mcol_character()[39m,
true = [31mcol_character()[39m,
true_prob = [32mcol_double()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 118"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 119"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 120"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 121"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 122"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
rowname = [31mcol_character()[39m,
Condition2 = [32mcol_double()[39m,
method = [31mcol_character()[39m,
true = [31mcol_character()[39m,
true_prob = [32mcol_double()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 123"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 124"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 125"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 126"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 127"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 128"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 129"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 130"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 131"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 132"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 133"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 134"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 135"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 136"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 137"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 138"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 139"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
rowname = [31mcol_character()[39m,
Condition2 = [32mcol_double()[39m,
method = [31mcol_character()[39m,
true = [31mcol_character()[39m,
true_prob = [32mcol_double()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 140"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 141"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 142"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 143"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 144"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
rowname = [31mcol_character()[39m,
Condition2 = [32mcol_double()[39m,
method = [31mcol_character()[39m,
true = [31mcol_character()[39m,
true_prob = [32mcol_double()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 145"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 146"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 147"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 148"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 149"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
rowname = [31mcol_character()[39m,
Condition2 = [32mcol_double()[39m,
method = [31mcol_character()[39m,
true = [31mcol_character()[39m,
true_prob = [32mcol_double()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 150"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 151"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 152"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 153"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 154"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 155"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 156"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 157"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 158"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 159"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 160"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 161"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 162"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 163"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 164"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 165"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 166"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
rowname = [31mcol_character()[39m,
Condition2 = [32mcol_double()[39m,
method = [31mcol_character()[39m,
true = [31mcol_character()[39m,
true_prob = [32mcol_double()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 167"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 168"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 169"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 170"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 171"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
rowname = [31mcol_character()[39m,
Condition2 = [32mcol_double()[39m,
method = [31mcol_character()[39m,
true = [31mcol_character()[39m,
true_prob = [32mcol_double()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 172"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 173"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 174"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 175"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 176"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
rowname = [31mcol_character()[39m,
Condition2 = [32mcol_double()[39m,
method = [31mcol_character()[39m,
true = [31mcol_character()[39m,
true_prob = [32mcol_double()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 177"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 178"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 179"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 180"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 181"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 182"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 183"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 184"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 185"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 186"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 187"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 188"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 189"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 190"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 191"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 192"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 193"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
rowname = [31mcol_character()[39m,
Condition2 = [32mcol_double()[39m,
method = [31mcol_character()[39m,
true = [31mcol_character()[39m,
true_prob = [32mcol_double()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 194"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 195"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 196"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 197"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 198"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
rowname = [31mcol_character()[39m,
Condition2 = [32mcol_double()[39m,
method = [31mcol_character()[39m,
true = [31mcol_character()[39m,
true_prob = [32mcol_double()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 199"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 200"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 201"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 202"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 203"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
rowname = [31mcol_character()[39m,
Condition2 = [32mcol_double()[39m,
method = [31mcol_character()[39m,
true = [31mcol_character()[39m,
true_prob = [32mcol_double()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 204"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 205"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 206"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 207"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 208"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 209"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 210"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 211"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 212"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 213"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 214"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 215"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 216"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 217"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 218"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 219"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 220"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
rowname = [31mcol_character()[39m,
Condition2 = [32mcol_double()[39m,
method = [31mcol_character()[39m,
true = [31mcol_character()[39m,
true_prob = [32mcol_double()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 221"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 222"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 223"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 224"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 225"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
rowname = [31mcol_character()[39m,
Condition2 = [32mcol_double()[39m,
method = [31mcol_character()[39m,
true = [31mcol_character()[39m,
true_prob = [32mcol_double()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 226"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 227"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 228"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 229"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 230"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
rowname = [31mcol_character()[39m,
Condition2 = [32mcol_double()[39m,
method = [31mcol_character()[39m,
true = [31mcol_character()[39m,
true_prob = [32mcol_double()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 231"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 232"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 233"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 234"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 235"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 236"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 237"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 238"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 239"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 240"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 241"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 242"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 243"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
cluster_outcome_df
NA
pl_df <- cluster_outcome_df %>%
filter(method!="milo_batch") %>%
mutate(FDR = FP/(TP+FP)) %>%
mutate(TPR=ifelse(is.nan(TPR), 0, TPR),
FPR=ifelse(is.nan(FPR), 0, FPR),
FDR=ifelse(is.nan(FDR), 0, FDR),
Precision=ifelse(is.nan(Precision), 0, Precision)) %>%
mutate(pop=str_replace(pop, "_", " ")) %>%
mutate(pop=factor(pop, levels=unique(pop))) %>%
filter(DA_thresh >= 0.55 & batchEffect==0)
pl_right <- pl_df %>%
ggplot(aes(as.factor(round(prob2FC(as.numeric(enr)),1)), TPR, color=method)) +
geom_boxplot(outlier.alpha = 0) +
ggbeeswarm::geom_quasirandom(alpha=0.5, position="stack", size=0.5) +
theme_bw(base_size = 16) +
scale_color_manual(values = method_colors, labels=setNames(method_labels, method_names)) +
scale_fill_manual(values = method_colors, labels=setNames(method_labels, method_names)) +
facet_grid(.~method, labeller=pl_labeller) +
theme(#axis.text.x = element_blank(), axis.ticks.x = element_blank(),
axis.title.x = element_blank())
pl_left <- pl_df %>%
ggplot(aes(as.factor(round(prob2FC(as.numeric(enr)),1)), FDR, color=method)) +
geom_boxplot(outlier.alpha = 0) +
ggbeeswarm::geom_quasirandom(alpha=0.5, position="stack", size=0.5) +
geom_hline(yintercept = 0.1, linetype=2) +
theme_bw(base_size = 16) +
scale_color_manual(values = method_colors, labels=setNames(method_labels, method_names)) +
scale_fill_manual(values = method_colors, labels=setNames(method_labels, method_names)) +
facet_grid(.~method, labeller=pl_labeller) +
theme(#axis.text.x = element_blank(), axis.ticks.x = element_blank(),
axis.title.x = element_blank()
)
pl <- pl_right / pl_left +
plot_layout(guides='collect') &
theme(#axis.text.x=element_blank(), axis.ticks.x=element_blank(),
axis.title.x=element_blank()
)
pl
Plot UMAP
cluster_sce <- readRDS("~/data/milo_benchmark/cluster3x_data_bm.RDS")
indir <- "~/data/milo_benchmark/synthetic_data/"
names(reducedDims(cluster_sce))[2] <- "umap_batch"
colnames(reducedDims(cluster_sce)[[2]]) <- c("X1", "X2")
pl_top <- plot_outcome_umap(cluster_sce, method = 'milo', pop="B3", enr = 0.9, seed = 43,batchEffect = 0, true = TRUE, data_id="cluster3x") +
theme(legend.position="top")
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
rowname = [31mcol_character()[39m,
Block = [31mcol_character()[39m,
Replicate = [31mcol_character()[39m,
cell = [31mcol_character()[39m,
celltype = [31mcol_character()[39m,
synth_labels = [31mcol_character()[39m,
synth_samples = [31mcol_character()[39m,
synth_batches = [31mcol_character()[39m,
Condition1_prob = [32mcol_double()[39m,
Condition2_prob = [32mcol_double()[39m,
true_labels = [31mcol_character()[39m
)
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
plot_cluster <- ((pl_top) | (pl & theme(legend.position="top"))) +
plot_layout(widths = c(0.5,2))
plot_cluster
Assemble figure
fig <- (
(plot_cluster ) /
(plot_linear & theme(legend.position="none")) /
(plot_branch & theme(legend.position="none"))
) +
plot_layout() &
theme(strip.text = element_text(size=11))
fig +
ggsave(paste0(figdir, "simData_figure.png"), width=10, height = 13) +
ggsave(paste0(figdir, "simData_figure.pdf"), width=10, height = 13)
Check some examples
plot_outcome_umap(sce = linear_sce, method="louvain", pop="B3", enr=0.9, seed=43, batchEffect = '0', data_id = "cluster3x", true=FALSE) +
plot_outcome_umap(sce = linear_sce, method="cydar", pop="B3", enr=0.9, seed=43, batchEffect = '0', data_id = "cluster3x", true=FALSE) +
plot_outcome_umap(sce = linear_sce, method="milo", pop="B3", enr=0.9, seed=43, batchEffect = '0', data_id = "cluster3x", true=FALSE) +
plot_outcome_umap(sce = linear_sce, method="daseq", pop="B3", enr=0.9, seed=43, batchEffect = '0', data_id = "cluster3x", true=FALSE) +
plot_outcome_umap(sce = linear_sce, method="daseq", pop="B3", enr=0.9, seed=43, batchEffect = '0', data_id = "cluster3x", true=TRUE) +
plot_layout(guides="collect")
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
rowname = [31mcol_character()[39m,
Block = [31mcol_character()[39m,
Replicate = [31mcol_character()[39m,
cell = [31mcol_character()[39m,
celltype = [31mcol_character()[39m,
synth_labels = [31mcol_character()[39m,
synth_samples = [31mcol_character()[39m,
synth_batches = [31mcol_character()[39m,
Condition1_prob = [32mcol_double()[39m,
Condition2_prob = [32mcol_double()[39m,
true_labels = [31mcol_character()[39m
)
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
'-' not meaningful for factors
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
rowname = [31mcol_character()[39m,
Block = [31mcol_character()[39m,
Replicate = [31mcol_character()[39m,
cell = [31mcol_character()[39m,
celltype = [31mcol_character()[39m,
synth_labels = [31mcol_character()[39m,
synth_samples = [31mcol_character()[39m,
synth_batches = [31mcol_character()[39m,
Condition1_prob = [32mcol_double()[39m,
Condition2_prob = [32mcol_double()[39m,
true_labels = [31mcol_character()[39m
)
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
'-' not meaningful for factors
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
rowname = [31mcol_character()[39m,
Block = [31mcol_character()[39m,
Replicate = [31mcol_character()[39m,
cell = [31mcol_character()[39m,
celltype = [31mcol_character()[39m,
synth_labels = [31mcol_character()[39m,
synth_samples = [31mcol_character()[39m,
synth_batches = [31mcol_character()[39m,
Condition1_prob = [32mcol_double()[39m,
Condition2_prob = [32mcol_double()[39m,
true_labels = [31mcol_character()[39m
)
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
'-' not meaningful for factors
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
rowname = [31mcol_character()[39m,
Block = [31mcol_character()[39m,
Replicate = [31mcol_character()[39m,
cell = [31mcol_character()[39m,
celltype = [31mcol_character()[39m,
synth_labels = [31mcol_character()[39m,
synth_samples = [31mcol_character()[39m,
synth_batches = [31mcol_character()[39m,
Condition1_prob = [32mcol_double()[39m,
Condition2_prob = [32mcol_double()[39m,
true_labels = [31mcol_character()[39m
)
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
'-' not meaningful for factors
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
rowname = [31mcol_character()[39m,
Block = [31mcol_character()[39m,
Replicate = [31mcol_character()[39m,
cell = [31mcol_character()[39m,
celltype = [31mcol_character()[39m,
synth_labels = [31mcol_character()[39m,
synth_samples = [31mcol_character()[39m,
synth_batches = [31mcol_character()[39m,
Condition1_prob = [32mcol_double()[39m,
Condition2_prob = [32mcol_double()[39m,
true_labels = [31mcol_character()[39m
)
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
Comparing accuracy and precision of the fold-change estimates of the two methods running MELD and Milo on the same simulation on the embryo data.
We estimate LFCs for both methods (see run_miloVSmeld.R) and compare with the true LFC
## Mean squared error
MSE <- function(true, pred){
mean((true - pred)^2)
}
## Mean bias error
MBE <- function(true, pred){
mean(true - pred)
}
## Mean abs error
MAE <- function(true, pred){
mean(abs(true - pred))
}
## std error
SE <- function(true, pred){
sqrt((sum((true - pred)^2))/(length(pred) - 2))
}
## Convert condition probability to LFC
prob2FC <- function(prob){
log((prob)/(1 - prob))
}
lfc_comparison <- function(milo_out, meld_out){
# ## Annotate nhoods that overlap true DA cells
# milo_out$DAres <- annotateNhoods(milo_out$Milo, milo_out$DAres, coldata_col = "true_labels")
## Take probability estimate at nhood indices
## (taking the avg of cells in the nhood gives equivalent results)
# nh_meld <- meld_out[unlist(nhoodIndex(milo_out$Milo)),]
nh_meld <- meld_out[milo_out$nhoodIndex,]
## Convert probabilities to LFC
lfc_df <- nh_meld %>%
mutate(milo_LFC=milo_out$logFC,
milo_signif=milo_out$SpatialFDR < 0.1,
true_labels=milo_out$true_labels,
nh_size=milo_out$nh_size
) %>%
mutate(true_LFC=prob2FC(true_prob), meld_LFC=prob2FC(Condition2)) %>%
select(- method, - true_prob, - Condition2) %>%
pivot_longer(cols=c(milo_LFC, meld_LFC), names_to="method", values_to="estimated_LFC")
lfc_df
}
## Load results from run_miloVSmeld.R
data_dir <- '/nfs/team205/ed6/data/milo_benchmark/MELDvsMilo/'
milo_files <- list.files(data_dir, pattern="milo.+csv", full.names = TRUE)
milo_res_outs <- lapply(milo_files, read_csv)
meld_files <- str_remove_all(milo_files, paste0(data_dir, "/")) %>%
str_replace("milo", "meld") %>%
paste0(data_dir, .)
meld_outs <- lapply(meld_files, read_csv)
meldVSmilo_meta <- data.frame(file_id = str_remove_all(meld_files, paste0(data_dir, "|/|benchmark_embryo_pop_|.csv"))) %>%
separate(col = file_id, sep = ".DAresults.", into=c("file_id", "method")) %>%
separate(col = file_id, sep = "_enr", into=c("pop", "file_id")) %>%
separate(col = file_id, sep = "_", into=c("enr", "seed", "batchEffect")) %>%
separate(col = method, sep = "\\.", into=c("method", 'k')) %>%
mutate(seed=str_remove(seed, "seed"),
k=as.numeric(str_remove(k, "k")),
batchEffect=str_remove(batchEffect, "batchEffect"),
) %>%
select(- method)
lfc_df <- lapply(seq_along(milo_res_outs), function(i) lfc_comparison(milo_res_outs[[i]], meld_outs[[i]]) %>%
bind_cols(meldVSmilo_meta[i,])) %>%
purrr::reduce(bind_rows)
pl_labeller <- labeller(
enr = enr_labeller2,
true_labels = label_value,
pop = label_value,
.default = label_both
)
pl_milo <- lfc_df %>%
filter(pop %in% c("Gut", "Erythroid1", "Somitic_mesoderm")) %>%
filter(method=="milo_LFC" & batchEffect=='0') %>%
group_by(enr, true_labels, pop, k) %>%
mutate(MAE = MAE(true_LFC, estimated_LFC)) %>%
ggplot(aes(true_LFC, estimated_LFC)) +
geom_point(size=0.6, aes(color=true_labels)) +
geom_hline(yintercept = 0, linetype=2) +
geom_vline(xintercept = 0, linetype=2) +
geom_abline(linetype=2) +
scale_color_manual(values=c(NegLFC="red", NotDA="grey"), labels=c(NegLFC="NegLFC", NotDA="no DA"), name='') +
guides(color=guide_legend(override.aes = c(size=2))) +
facet_grid(pop~enr, labeller = pl_labeller) +
xlab("True LFC") + ylab("Milo estimated LFC") +
theme_bw(base_size = 14)
pl_meld <- lfc_df %>%
filter(pop %in% c("Gut", "Erythroid1", "Somitic_mesoderm")) %>%
filter(method=="meld_LFC" & batchEffect=='0') %>%
# filter(enr==0.9 & k==50 & true_labels=="NegLFC")
group_by(enr, true_labels, pop, k) %>%
mutate(MAE = MAE(true_LFC, estimated_LFC)) %>%
ggplot(aes(true_LFC, estimated_LFC)) +
geom_point(size=0.6, aes(color=true_labels)) +
geom_hline(yintercept = 0, linetype=2) +
geom_vline(xintercept = 0, linetype=2) +
geom_abline(linetype=2) +
xlab("True LFC") + ylab("MELD estimated LFC") +
guides(color=guide_legend(override.aes = c(size=2))) +
scale_color_manual(values=c(NegLFC="red", NotDA="grey"), labels=c(NegLFC="NegLFC", NotDA="no DA"), name="") +
facet_grid(pop~enr, labeller = pl_labeller) +
theme_bw(base_size = 14)
pl_left <- (pl_milo | pl_meld) +
plot_layout(guides="collect") &
theme(legend.position="top", legend.justification = c(1,1))
pl_milo <- lfc_df %>%
filter(pop %in% c("Gut", "Erythroid1", "Somitic_mesoderm")) %>%
filter(method=="milo_LFC" & batchEffect=='0.5') %>%
group_by(enr, true_labels, pop, k) %>%
mutate(MAE = MAE(true_LFC, estimated_LFC)) %>%
ggplot(aes(true_LFC, estimated_LFC)) +
geom_point(size=0.6, aes(color=true_labels)) +
geom_hline(yintercept = 0, linetype=2) +
geom_vline(xintercept = 0, linetype=2) +
geom_abline(linetype=2) +
scale_color_manual(values=c(NegLFC="red", NotDA="grey"), labels=c(NegLFC="NegLFC", NotDA="no DA"), name='') +
guides(color=guide_legend(override.aes = c(size=2))) +
facet_grid(pop~enr, labeller = pl_labeller) +
xlab("True LFC") + ylab("Milo estimated LFC") +
theme_bw(base_size = 14)
pl_meld <- lfc_df %>%
filter(pop %in% c("Gut", "Erythroid1", "Somitic_mesoderm")) %>%
filter(method=="meld_LFC" & batchEffect=='0.5') %>%
# filter(enr==0.9 & k==50 & true_labels=="NegLFC")
group_by(enr, true_labels, pop, k) %>%
mutate(MAE = MAE(true_LFC, estimated_LFC)) %>%
ggplot(aes(true_LFC, estimated_LFC)) +
geom_point(size=0.6, aes(color=true_labels)) +
geom_hline(yintercept = 0, linetype=2) +
geom_vline(xintercept = 0, linetype=2) +
geom_abline(linetype=2) +
xlab("True LFC") + ylab("MELD estimated LFC") +
guides(color=guide_legend(override.aes = c(size=2))) +
scale_color_manual(values=c(NegLFC="red", NotDA="grey"), labels=c(NegLFC="NegLFC", NotDA="no DA"), name="") +
facet_grid(pop~enr, labeller = pl_labeller) +
theme_bw(base_size = 14)
pl_left_be <- (pl_milo | pl_meld) +
plot_layout(guides="collect") &
theme(legend.position="top", legend.justification = c(1,1))
pl_right1 <- lfc_df %>%
filter(k==50) %>%
group_by(method, pop, true_labels, k, enr, batchEffect) %>%
summarise(MSE = MSE(true_LFC, estimated_LFC), sd=sd(abs(true_LFC - estimated_LFC))) %>%
ungroup() %>%
mutate(method = str_remove(method,"_LFC")) %>%
rename(`Batch effect \nmagnitude` = batchEffect) %>%
filter(true_labels=="NotDA") %>%
ggplot(aes(as.factor(round(prob2FC(as.numeric(enr)), 1)), MSE, color = method)) +
geom_boxplot() +
facet_grid(true_labels~`Batch effect \nmagnitude`, labeller=pl_labeller) +
theme_bw(base_size=18) +
xlab("Simulated log-Fold Change") +
scale_color_methods() +
theme(legend.position="top", legend.justification = c(1,1)) +
ylim(0,2.1)
pl_right2 <- lfc_df %>%
filter(k==50) %>%
group_by(method, pop, true_labels, k, enr, batchEffect) %>%
summarise(MSE = MSE(true_LFC, estimated_LFC), sd=sd(abs(true_LFC - estimated_LFC))) %>%
ungroup() %>%
mutate(method = str_remove(method,"_LFC")) %>%
rename(`Batch effect \nmagnitude` = batchEffect) %>%
filter(true_labels=="NegLFC") %>%
ggplot(aes(as.factor(round(prob2FC(as.numeric(enr)), 1)), MSE, color = method)) +
geom_boxplot() +
facet_grid(true_labels~`Batch effect \nmagnitude`, labeller=pl_labeller) +
theme_bw(base_size=18) +
xlab("Simulated log-Fold Change") +
scale_color_methods() +
theme(legend.position="top", legend.justification = c(1,1)) +
ylim(0,2.1)
pl_right <- pl_right1 + pl_right2 +
plot_layout(guides="collect") &
theme(legend.position="top", legend.justification = c(1,1))
(pl_left /pl_left_be / pl_right) +
plot_layout(heights=c(1.5, 1.5, 1)) +
plot_annotation(tag_levels = "A") +
# ggsave("~/mount/gdrive/milo/Figures/benchmark_v2/SFig_MELDvsMilo.pdf", width = 15, height = 16) +
ggsave("~/mount/gdrive/milo/Figures/resubmission/supplementary/suppl_fig_meldVSmilo.pdf", width = 15, height = 19)
ggsave("~/mount/gdrive/milo/Figures/benchmark_v2/SFig_MELDvsMilo.png", width = 15, height = 16)
## Read outputs
outdir <- "/nfs/team205/ed6/data/milo_benchmark/embryo/"
res_files <- list.files(outdir, pattern=".DAresults")
res_files_full <- list.files(outdir, pattern=".DAresults", full.names = TRUE)
# in_files <- list.files("~/data/milo_benchmark/synthetic_data/", pattern="coldata.csv")
## Make data frame w benchmark parameters
out_meta_df <- data.frame(file_id = str_remove_all(res_files, "benchmark_embryo_pop_|.csv")) %>%
separate(col = file_id, sep = ".DAresults.", into=c("file_id", "method")) %>%
separate(col = file_id, sep = "_enr", into=c("pop", "file_id")) %>%
separate(col = file_id, sep = "_", into=c("enr", "seed", "batchEffect")) %>%
mutate(seed=str_remove(seed, "seed"), batchEffect=str_remove_all(batchEffect, "batchEffect"))
## Read benchmark results w/o batch effects
no_batch_files <- str_detect(res_files_full, "batchEffect0.DAresult") & !str_detect(res_files_full, "louvain_batch|cydar_batch|milo_batch")
# prob_thresh_vec <- seq(0.5, 0.9, 0.05)
outcome_df <- lapply(seq_along(res_files_full[no_batch_files]), function(i){
print(paste("Outcome no. ", i))
benchmark_df <- read_csv(res_files_full[no_batch_files][i])
pop_enr <- as.numeric(out_meta_df[no_batch_files,][i,"enr"])
benchmark_df %>%
.outcome_by_prob(da_upper = embryo_thresh) %>%
mutate(DA_thresh=embryo_thresh) %>%
ungroup() %>%
dplyr::select(- method) %>%
bind_cols(out_meta_df[no_batch_files,][i,]) %>%
filter(DA_thresh < as.numeric(enr))
}) %>%
purrr::reduce(bind_rows)
write_csv(outcome_df, "/nfs/team205/ed6/data/milo_benchmark/outcome_embryo_v3_noBatch.csv")
Read outcome for embryo (built with wrapper build_outcome.R)
outcome_df <- read_csv("/nfs/team205/ed6/data/milo_benchmark/outcome_embryo_v3_noBatch.csv")
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
FN = [32mcol_double()[39m,
TN = [32mcol_double()[39m,
TP = [32mcol_double()[39m,
FP = [32mcol_double()[39m,
TPR = [32mcol_double()[39m,
FPR = [32mcol_double()[39m,
TNR = [32mcol_double()[39m,
FNR = [32mcol_double()[39m,
FDR = [32mcol_double()[39m,
Precision = [32mcol_double()[39m,
Power = [32mcol_double()[39m,
Accuracy = [32mcol_double()[39m,
DA_thresh = [32mcol_double()[39m,
pop = [31mcol_character()[39m,
enr = [32mcol_double()[39m,
seed = [32mcol_double()[39m,
batchEffect = [32mcol_double()[39m,
method = [31mcol_character()[39m
)
outcome_df <- outcome_df %>%
filter(DA_thresh==embryo_thresh) %>%
filter(pop!="Mixed_mesoderm")
# enr_labeller2 <- function(variable, value, split_lines=FALSE){
# fc <- round(prob2FC(as.numeric(value)), 2)
# enr_name <- paste("logFC = ", fc)
# return(enr_name)
# }
pl_df <- outcome_df %>%
filter(batchEffect==0 & str_detect(method, "_batch", negate = TRUE)) %>%
mutate(FDR = FP/(TP+FP)) %>%
mutate(TPR=ifelse(is.nan(TPR), 0, TPR),
FPR=ifelse(is.nan(FPR), 0, FPR),
FDR=ifelse(is.nan(FDR), 0, FDR),
Precision=ifelse(is.nan(Precision), 0, Precision)) %>%
filter(DA_thresh >= embryo_thresh & batchEffect==0) %>%
mutate(enr=as.character(enr))
p_top <- pl_df %>%
filter(batchEffect=="0") %>%
ggplot(aes(as.factor(round(prob2FC(as.numeric(enr)),1)), TPR, color=method)) +
geom_boxplot(outlier.alpha = 0) +
ggbeeswarm::geom_quasirandom(alpha=0.5, position="stack", size=0.5) +
# geom_hline(yintercept = 0.1, linetype=2) +
theme_bw(base_size = 16) +
scale_color_manual(values = method_colors, labels=setNames(method_labels, method_names)) +
scale_fill_manual(values = method_colors, labels=setNames(method_labels, method_names)) +
facet_grid(.~method, labeller=pl_labeller) +
theme(axis.text.x = element_blank(), axis.ticks.x = element_blank(), axis.title.x = element_blank())
p_bottom <- pl_df %>%
filter(batchEffect=="0") %>%
ggplot(aes(as.factor(round(prob2FC(as.numeric(enr)),1)), FDR, color=method)) +
geom_boxplot(outlier.alpha = 0) +
ggbeeswarm::geom_quasirandom(alpha=0.5, position="stack", size=0.5) +
geom_hline(yintercept = 0.1, linetype=2) +
theme_bw(base_size = 16) +
scale_color_manual(values = method_colors, labels=setNames(method_labels, method_names)) +
scale_fill_manual(values = method_colors, labels=setNames(method_labels, method_names)) +
facet_grid(.~method, labeller=pl_labeller) +
xlab('Simulated log-Fold Change')
(p_top / p_bottom) + plot_layout(guides="collect") +
ggsave("~/mount/gdrive/milo/Figures/benchmark_v2/bm_nobatch.pdf", width = 11, height = 6) +
ggsave("~/mount/gdrive/milo/Figures/benchmark_v2/bm_nobatch.png", width = 11, height = 6)
Range of sizes
mutate(outcome_df, nDA= TP+FN) %>%
filter(method=="milo" & batchEffect=="0") %>%
summarise(min(nDA))
ggplot(aes(nDA,TPR)) +
geom_point()
Generate labels
I pick Erythroid2 and Caudal_neurectoderm as the best and worse performance regions
save_labels_capped <- function(sce, cap_enr, pop, seed, a_logit){
if (str_detect(pop, "_")) {
pop <- str_replace(pop, "_", " ")
}
sce <- add_synthetic_labels_pop(sce, pop=pop, pop_column = "celltype", seed=seed, pop_enr=0.9, cap_enr = cap_enr,a_logit = a_logit)
true_labels <- ifelse(sce$Condition1_prob < (1-cap_enr), "NegLFC", ifelse(sce$Condition2_prob > cap_enr, "PosLFC", "NotDA"))
colData(sce)[["true_labels"]] <- true_labels
if (str_detect(pop, " ")) {
pop <- str_replace(pop, " ", "_")
}
## Save coldata
outdir <-'/nfs/team205/ed6/data/milo_benchmark/synthetic_data/'
a <- str_remove(as.character(a_logit), "\\.")
outprefix <- str_c("benchmark_embryo_pop_", pop, '_enr', cap_enr, "_seed", seed, "_capped_logit", a)
coldata <- data.frame(colData(sce)) %>% rownames_to_column()
write_csv(coldata, str_c(outdir, outprefix, ".coldata.csv"))
}
sce <- embryo_sce
## Exclude mixed mesoderm (it's too mixed)
pops <- c("Erythroid2", "Caudal_neurectoderm")
for (p in pops) {
for (e in seq(0.75,0.95, by=0.1) ) {
for (s in c(43,44,45) ) {
for (a in c(0.3,0.5, 0.7) ) {
save_labels_capped(embryo_sce, e, p, s, a)
}
}
}
}
I run the benchmark with synthetic labels generated above (see submit_benchmark_capped.sh)
Read all results
outdir <- "/nfs/team205/ed6/data/milo_benchmark/capped_logit/"
res_files <- list.files(outdir, pattern=".+DAresults.+.csv")
res_files_full <- list.files(outdir, pattern=".+DAresults.+.csv", full.names = TRUE)
# in_files <- list.files("~/data/milo_benchmark/synthetic_data/", pattern="_enr0.[78].+coldata.csv")
## Make data frame w benchmark parameters
capped_out_meta_df <- data.frame(file_id = str_remove_all(res_files, "benchmark_embryo_pop_|.csv")) %>%
separate(col = file_id, sep = ".DAresults.", into=c("file_id", "method")) %>%
separate(col = file_id, sep = "_enr", into=c("pop", "file_id")) %>%
separate(col = file_id, sep = "_", into=c("enr", "seed",'capped','logit', "batchEffect")) %>%
mutate(seed=str_remove(seed, "seed"), batchEffect=str_remove(batchEffect, "batchEffect"),
logit=str_remove(logit, "logit"))
## Load results
capped_outcome_df <- lapply(seq_along(res_files_full), function(i){
print(paste("Outcome no. ", i))
benchmark_df <- read_csv(res_files_full[i]) %>%
.outcome_by_prob(da_upper = embryo_thresh) %>%
mutate(DA_thresh=embryo_thresh) %>%
ungroup() %>%
dplyr::select(- method) %>%
bind_cols(capped_out_meta_df[i,])
pop_enr <- as.numeric(capped_out_meta_df[i,"enr"])
benchmark_df
}) %>%
purrr::reduce(bind_rows)
outcome_df_popsize <- capped_outcome_df
## Merge with benchmark outcomes
pl_df <- outcome_df_popsize %>%
filter(str_detect(method, "_batch", negate = TRUE)) %>%
mutate(FDR = FP/(TP+FP)) %>%
mutate(TPR=ifelse(is.nan(TPR), 0, TPR),
FPR=ifelse(is.nan(FPR), 0, FPR),
FDR=ifelse(is.nan(FDR), 0, FDR),
Precision=ifelse(is.nan(Precision), 0, Precision)) %>%
# mutate(pop=str_replace(pop, "_", " ")) %>%
left_join(DA_pop_size_df) %>%
arrange(pop_size) %>%
mutate(pop=factor(pop, levels=unique(pop))) %>%
mutate(enr=as.character(enr))
Joining, by = c("pop", "enr", "seed", "logit")
Due to low signal to noise ratio for certain simulations
## Read benchmark results w/o batch effects and selecting just top and bottom population
keep_pops <- c("Erythroid2", "Caudal_neurectoderm")
keep_files <- str_detect(res_files_full, "batchEffect0.DAresult") &
!str_detect(res_files_full, "louvain_batch|cydar_batch|milo_batch") &
str_detect(res_files_full, paste0(keep_pops, collapse = "|"))
suppressWarnings({
outcome_df_2 <- lapply(seq_along(res_files_full[keep_files]), function(i){
print(paste("Outcome no. ", i))
benchmark_df <- read_csv(res_files_full[keep_files][i])
pop_enr <- as.numeric(out_meta_df[keep_files,][i,"enr"])
benchmark_df <- benchmark_df %>%
mutate(true = ifelse(benchmark_df$true_prob < 1-embryo_thresh, "NegLFC", ifelse(benchmark_df$true_prob > embryo_thresh, "PosLFC", "NotDA")))
## Check if conditions were swapped in test
pred_cor <- benchmark_df %>%
group_by(pred) %>%
summarise(m=mean(true_prob)) %>%
ungroup() %>%
mutate(pred=factor(pred, levels=c("NegLFC", "NotDA", "PosLFC"), ordered = TRUE)) %>%
mutate(pred=as.numeric(pred)) %>%
summarise(c=cor(pred, m)) %>%
pull(c)
## Swap outcomes if so
if (!is.na(pred_cor)) {
if (pred_cor < 0) {
benchmark_df <- mutate(benchmark_df, pred = ifelse(pred=="NegLFC", "PosLFC", ifelse(pred=="PosLFC", "NegLFC", "NotDA")))
}
}
benchmark_df %>%
mutate(prob_bins=cut(1-true_prob, breaks = seq(0.3, 1, by=0.05), include.lowest = TRUE, right=FALSE)) %>%
group_by(prob_bins) %>%
do(calculate_outcome(.)) %>%
ungroup() %>%
dplyr::select(- method) %>%
bind_cols(out_meta_df[no_batch_files,][i,])
}) %>%
purrr::reduce(bind_rows)
})
[1] "Outcome no. 1"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 2"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 3"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 4"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 5"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 6"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 7"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 8"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 9"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 10"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 11"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 12"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 13"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 14"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 15"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 16"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 17"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 18"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 19"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 20"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 21"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 22"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 23"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 24"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 25"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 26"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 27"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 28"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 29"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 30"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 31"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 32"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 33"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 34"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 35"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 36"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 37"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 38"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 39"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 40"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 41"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 42"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 43"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 44"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 45"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 46"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 47"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 48"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 49"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 50"
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 51"
[36m──[39m [1m[1mColumn specification[1m[22m [36m────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 52"
[36m──[39m [1m[1mColumn specification[1m[22m [36m────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 53"
[36m──[39m [1m[1mColumn specification[1m[22m [36m────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 54"
[36m──[39m [1m[1mColumn specification[1m[22m [36m────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 55"
[36m──[39m [1m[1mColumn specification[1m[22m [36m────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 56"
[36m──[39m [1m[1mColumn specification[1m[22m [36m────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 57"
[36m──[39m [1m[1mColumn specification[1m[22m [36m────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 58"
[36m──[39m [1m[1mColumn specification[1m[22m [36m────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 59"
[36m──[39m [1m[1mColumn specification[1m[22m [36m────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 60"
[36m──[39m [1m[1mColumn specification[1m[22m [36m────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 61"
[36m──[39m [1m[1mColumn specification[1m[22m [36m────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 62"
[36m──[39m [1m[1mColumn specification[1m[22m [36m────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 63"
[36m──[39m [1m[1mColumn specification[1m[22m [36m────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 64"
[36m──[39m [1m[1mColumn specification[1m[22m [36m────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 65"
[36m──[39m [1m[1mColumn specification[1m[22m [36m────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 66"
[36m──[39m [1m[1mColumn specification[1m[22m [36m────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 67"
[36m──[39m [1m[1mColumn specification[1m[22m [36m────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 68"
[36m──[39m [1m[1mColumn specification[1m[22m [36m────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 69"
[36m──[39m [1m[1mColumn specification[1m[22m [36m────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 70"
[36m──[39m [1m[1mColumn specification[1m[22m [36m────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 71"
[36m──[39m [1m[1mColumn specification[1m[22m [36m────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 72"
[36m──[39m [1m[1mColumn specification[1m[22m [36m────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 73"
[36m──[39m [1m[1mColumn specification[1m[22m [36m────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 74"
[36m──[39m [1m[1mColumn specification[1m[22m [36m────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 75"
[36m──[39m [1m[1mColumn specification[1m[22m [36m────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 76"
[36m──[39m [1m[1mColumn specification[1m[22m [36m────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 77"
[36m──[39m [1m[1mColumn specification[1m[22m [36m────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 78"
[36m──[39m [1m[1mColumn specification[1m[22m [36m────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 79"
[36m──[39m [1m[1mColumn specification[1m[22m [36m────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 80"
[36m──[39m [1m[1mColumn specification[1m[22m [36m────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 81"
[36m──[39m [1m[1mColumn specification[1m[22m [36m────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 82"
[36m──[39m [1m[1mColumn specification[1m[22m [36m────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 83"
[36m──[39m [1m[1mColumn specification[1m[22m [36m────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 84"
[36m──[39m [1m[1mColumn specification[1m[22m [36m────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 85"
[36m──[39m [1m[1mColumn specification[1m[22m [36m────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 86"
[36m──[39m [1m[1mColumn specification[1m[22m [36m────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 87"
[36m──[39m [1m[1mColumn specification[1m[22m [36m────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 88"
[36m──[39m [1m[1mColumn specification[1m[22m [36m────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 89"
[36m──[39m [1m[1mColumn specification[1m[22m [36m────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 90"
[36m──[39m [1m[1mColumn specification[1m[22m [36m────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 91"
[36m──[39m [1m[1mColumn specification[1m[22m [36m────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 92"
[36m──[39m [1m[1mColumn specification[1m[22m [36m────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 93"
[36m──[39m [1m[1mColumn specification[1m[22m [36m────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 94"
[36m──[39m [1m[1mColumn specification[1m[22m [36m────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 95"
[36m──[39m [1m[1mColumn specification[1m[22m [36m────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 96"
[36m──[39m [1m[1mColumn specification[1m[22m [36m────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 97"
[36m──[39m [1m[1mColumn specification[1m[22m [36m────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 98"
[36m──[39m [1m[1mColumn specification[1m[22m [36m────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 99"
[36m──[39m [1m[1mColumn specification[1m[22m [36m────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 100"
[36m──[39m [1m[1mColumn specification[1m[22m [36m────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 101"
[36m──[39m [1m[1mColumn specification[1m[22m [36m────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 102"
[36m──[39m [1m[1mColumn specification[1m[22m [36m────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 103"
[36m──[39m [1m[1mColumn specification[1m[22m [36m────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 104"
[36m──[39m [1m[1mColumn specification[1m[22m [36m────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 105"
[36m──[39m [1m[1mColumn specification[1m[22m [36m────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 106"
[36m──[39m [1m[1mColumn specification[1m[22m [36m────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 107"
[36m──[39m [1m[1mColumn specification[1m[22m [36m────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 108"
[36m──[39m [1m[1mColumn specification[1m[22m [36m────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 109"
[36m──[39m [1m[1mColumn specification[1m[22m [36m────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 110"
[36m──[39m [1m[1mColumn specification[1m[22m [36m────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 111"
[36m──[39m [1m[1mColumn specification[1m[22m [36m────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 112"
[36m──[39m [1m[1mColumn specification[1m[22m [36m────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 113"
[36m──[39m [1m[1mColumn specification[1m[22m [36m────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 114"
[36m──[39m [1m[1mColumn specification[1m[22m [36m────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 115"
[36m──[39m [1m[1mColumn specification[1m[22m [36m────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 116"
[36m──[39m [1m[1mColumn specification[1m[22m [36m────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 117"
[36m──[39m [1m[1mColumn specification[1m[22m [36m────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 118"
[36m──[39m [1m[1mColumn specification[1m[22m [36m────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 119"
[36m──[39m [1m[1mColumn specification[1m[22m [36m────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 120"
[36m──[39m [1m[1mColumn specification[1m[22m [36m────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 121"
[36m──[39m [1m[1mColumn specification[1m[22m [36m────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 122"
[36m──[39m [1m[1mColumn specification[1m[22m [36m────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 123"
[36m──[39m [1m[1mColumn specification[1m[22m [36m────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 124"
[36m──[39m [1m[1mColumn specification[1m[22m [36m────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 125"
[36m──[39m [1m[1mColumn specification[1m[22m [36m────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 126"
[36m──[39m [1m[1mColumn specification[1m[22m [36m────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 127"
[36m──[39m [1m[1mColumn specification[1m[22m [36m────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 128"
[36m──[39m [1m[1mColumn specification[1m[22m [36m────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 129"
[36m──[39m [1m[1mColumn specification[1m[22m [36m────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 130"
[36m──[39m [1m[1mColumn specification[1m[22m [36m────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 131"
[36m──[39m [1m[1mColumn specification[1m[22m [36m────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 132"
[36m──[39m [1m[1mColumn specification[1m[22m [36m────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 133"
[36m──[39m [1m[1mColumn specification[1m[22m [36m────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 134"
[36m──[39m [1m[1mColumn specification[1m[22m [36m────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 135"
[36m──[39m [1m[1mColumn specification[1m[22m [36m────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 136"
[36m──[39m [1m[1mColumn specification[1m[22m [36m────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 137"
[36m──[39m [1m[1mColumn specification[1m[22m [36m────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 138"
[36m──[39m [1m[1mColumn specification[1m[22m [36m────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 139"
[36m──[39m [1m[1mColumn specification[1m[22m [36m────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 140"
[36m──[39m [1m[1mColumn specification[1m[22m [36m────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 141"
[36m──[39m [1m[1mColumn specification[1m[22m [36m────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 142"
[36m──[39m [1m[1mColumn specification[1m[22m [36m────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 143"
[36m──[39m [1m[1mColumn specification[1m[22m [36m────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
[1] "Outcome no. 144"
[36m──[39m [1m[1mColumn specification[1m[22m [36m────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
`summarise()` has grouped output by 'method'. You can override using the `.groups` argument.
outcome_df_2
pl_signal2noise <- function(mypop, myenr, myseed, mymethod){
if (mymethod=="daseq") {
pos_outcome <- "PosLFC"
} else {
pos_outcome <- "NegLFC"
}
popTPR <- outcome_df %>% filter(pop==mypop & enr==myenr & seed==myseed & method==mymethod) %>% pull(TPR)
res_file <- list.files(outdir,
pattern= paste0(".+",'embryo',"_pop_", mypop, "_enr",myenr,"_seed", myseed, '.+batchEffect0',".DAresults.",mymethod,".csv"),
full.names = TRUE)
pl <- read_csv(res_file) %>%
mutate(outcome = case_when(pred=="NotDA" & true_prob < 1-embryo_thresh ~ "FN",
pred==pos_outcome & true_prob < 1-embryo_thresh ~ "TP",
pred=="NotDA" & true_prob > 1-embryo_thresh ~ "TN"
)) %>%
filter(outcome %in% c('TP', "FN")) %>%
ggplot(aes(1 - true_prob, color=outcome)) +
geom_density(size=1) +
xlab("P(C1)") +
ggtitle(paste("TPR = ", round(popTPR,2))) +
theme_bw(base_size = 14)
pl
}
pl_top <- wrap_plots(lapply(c(0.75, 0.85, 0.95), function(x) pl_signal2noise("Erythroid2", x, myseed = 43, mymethod = "milo")), ncol=3)
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
pl_bot <- wrap_plots(lapply(c(0.75, 0.85, 0.95), function(x) pl_signal2noise("Caudal_neurectoderm", x, myseed = 43, mymethod = "milo")), ncol=3)
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
true_prob = [32mcol_double()[39m,
true = [31mcol_character()[39m,
method = [31mcol_character()[39m,
pred = [31mcol_character()[39m
)
pl_B <- (pl_top / pl_bot) +
plot_layout(guides = "collect")
pl_B +
ggsave(paste0(figdir,"Sfig_signal2noise.pdf"), height = 6, width = 9) +
ggsave(paste0(figdir,"Sfig_signal2noise.png"), height = 6, width = 9)
Read outcome for embryo (built with wrapper build_outcome.R)
outcome_df <- read_csv("/nfs/team205/ed6/data/milo_benchmark/outcome_embryo_v3_noBatch.csv")
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
FN = [32mcol_double()[39m,
TN = [32mcol_double()[39m,
TP = [32mcol_double()[39m,
FP = [32mcol_double()[39m,
TPR = [32mcol_double()[39m,
FPR = [32mcol_double()[39m,
TNR = [32mcol_double()[39m,
FNR = [32mcol_double()[39m,
FDR = [32mcol_double()[39m,
Precision = [32mcol_double()[39m,
Power = [32mcol_double()[39m,
Accuracy = [32mcol_double()[39m,
DA_thresh = [32mcol_double()[39m,
pop = [31mcol_character()[39m,
enr = [32mcol_double()[39m,
seed = [32mcol_double()[39m,
batchEffect = [32mcol_double()[39m,
method = [31mcol_character()[39m
)
Read outcomes (made with wrapper build_outcome.R)
outcome_df_be <- read_csv("/nfs/team205/ed6/data/milo_benchmark/outcome_embryo_v3_wBatch.csv") %>%
filter(pop!="Mixed_mesoderm")
Missing column names filled in: 'X19' [19]
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
FN = [32mcol_double()[39m,
TN = [32mcol_double()[39m,
TP = [32mcol_double()[39m,
FP = [32mcol_double()[39m,
TPR = [32mcol_double()[39m,
FPR = [32mcol_double()[39m,
TNR = [32mcol_double()[39m,
FNR = [32mcol_double()[39m,
FDR = [32mcol_double()[39m,
Precision = [32mcol_double()[39m,
Power = [32mcol_double()[39m,
Accuracy = [32mcol_double()[39m,
DA_thresh = [32mcol_double()[39m,
pop = [31mcol_character()[39m,
enr = [32mcol_double()[39m,
seed = [32mcol_double()[39m,
batchEffect = [32mcol_double()[39m,
method = [31mcol_character()[39m,
X19 = [33mcol_logical()[39m
)
outcome_df <- bind_rows(outcome_df, outcome_df_be)
batch_labeller <- as_labeller(c(milo="Milo\n(~ batch + condition)", louvain="Louvain\n(~ batch + condition)", cydar="Cydar", daseq='DAseq'))
pl_df <- outcome_df %>%
filter(method != "milo" & method != "louvain" & method != "cydar_batch") %>%
mutate(FDR = FP/(TP+FP)) %>%
mutate(TPR=ifelse(is.nan(TPR), 0, TPR),
FPR=ifelse(is.nan(FPR), 0, FPR),
FDR=ifelse(is.nan(FDR), 0, FDR),
Precision=ifelse(is.nan(Precision), 0, Precision)) %>%
mutate(method=str_remove(method,"_batch")) %>%
filter(enr >= 0.8) %>%
mutate(enr=as.character(enr))
p_top <- pl_df %>%
ggplot(aes(as.factor(batchEffect), TPR, color=method)) +
geom_boxplot(outlier.alpha = 0) +
ggbeeswarm::geom_quasirandom(alpha=0.5, position="stack", size=0.5) +
theme_bw(base_size = 16) +
scale_color_manual(values = method_colors, labels=setNames(method_labels, method_names)) +
scale_fill_manual(values = method_colors, labels=setNames(method_labels, method_names)) +
facet_grid(.~method, labeller=batch_labeller) +
theme(axis.text.x = element_blank(), axis.ticks.x = element_blank(), axis.title.x = element_blank())
p_bottom <- pl_df %>%
ggplot(aes(as.factor(batchEffect), FDR, color=method)) +
geom_boxplot(outlier.alpha = 0) +
ggbeeswarm::geom_quasirandom(alpha=0.5, position="stack", size=0.5) +
geom_hline(yintercept = 0.1, linetype=2) +
theme_bw(base_size = 16) +
scale_color_manual(values = method_colors, labels=setNames(method_labels, method_names)) +
scale_fill_manual(values = method_colors, labels=setNames(method_labels, method_names)) +
xlab("Batch effect magnitude") +
facet_grid(.~method, labeller=batch_labeller)
(p_top / p_bottom) + plot_layout(guides="collect") +
ggsave(paste0(figdir, "main_bm_batch.pdf"), width = 11, height = 6) +
ggsave(paste0(figdir, "main_bm_batch.png"), width = 11, height = 6)
Break down by logFC
pl_df <- outcome_df %>%
filter(method != "milo" & method != "louvain" & method != "cydar_batch") %>%
mutate(FDR = FP/(TP+FP)) %>%
mutate(TPR=ifelse(is.nan(TPR), 0, TPR),
FPR=ifelse(is.nan(FPR), 0, FPR),
FDR=ifelse(is.nan(FDR), 0, FDR),
Precision=ifelse(is.nan(Precision), 0, Precision)) %>%
mutate(method=str_remove(method,"_batch")) %>%
mutate(enr=as.character(enr))
p_top <- pl_df %>%
ggplot(aes(as.factor(batchEffect), TPR, color=method)) +
geom_boxplot(outlier.alpha = 0) +
ggbeeswarm::geom_quasirandom(alpha=0.5, position="stack", size=0.5) +
theme_bw(base_size = 16) +
scale_color_manual(values = method_colors, labels=setNames(method_labels, method_names)) +
scale_fill_manual(values = method_colors, labels=setNames(method_labels, method_names)) +
facet_grid(enr~method, labeller=labeller(enr=enr_labeller2, method=batch_labeller)) +
xlab("Batch effect magnitude")
p_bottom <- pl_df %>%
ggplot(aes(as.factor(batchEffect), FDR, color=method)) +
geom_boxplot(outlier.alpha = 0) +
ggbeeswarm::geom_quasirandom(alpha=0.5, position="stack", size=0.5) +
geom_hline(yintercept = 0.1, linetype=2) +
theme_bw(base_size = 16) +
scale_color_manual(values = method_colors, labels=setNames(method_labels, method_names)) +
scale_fill_manual(values = method_colors, labels=setNames(method_labels, method_names)) +
xlab("Batch effect magnitude") +
facet_grid(enr~method, labeller=labeller(enr=enr_labeller2, method=batch_labeller))
(p_top | p_bottom) + plot_layout(guides="collect") + plot_annotation(tag_levels = c("A")) +
# ggsave(paste0(figdir, "suppl_bm_batch_logFC.pdf"), width = 15, height = 10) +
# ggsave(paste0(figdir, "suppl_bm_batch_logFC.png"), width = 15, height = 10)
ggsave(paste0("~/mount/gdrive/milo/Figures/resubmission2/supplementary/suppl_fig_bm_batch.pdf"), width = 18, height = 10)
W and w/o batch control
pl_df <- outcome_df %>%
filter(method %in% c("milo", "milo_batch")) %>%
mutate(FDR = FP/(TP+FP)) %>%
mutate(TPR=ifelse(is.nan(TPR), 0, TPR),
FPR=ifelse(is.nan(FPR), 0, FPR),
FDR=ifelse(is.nan(FDR), 0, FDR),
Precision=ifelse(is.nan(Precision), 0, Precision)) %>%
mutate(design = ifelse(str_detect(method,"_batch"), "~ batch + condition", "~ condition")) %>%
filter(enr >= 0.8) %>%
mutate(enr=as.character(enr))
metric='TPR'
pl_left <-pl_df %>%
mutate(group=paste(method, design)) %>%
mutate(method=str_remove(method, "_batch")) %>%
ggplot(aes(as.factor(batchEffect), TPR, color =method)) +
geom_boxplot(outlier.alpha = 0) +
ggbeeswarm::geom_quasirandom(alpha=0.5, position="stack", size=0.5) +
facet_grid(.~design) +
theme_bw(base_size=16) +
geom_hline(yintercept = 0.8, linetype=2) +
# scale_color_manual(values = c(`~ condition`=method_colors["milo"], "black"))
scale_color_manual(values = method_colors, labels=c(milo="Milo", louvain="Louvain", cydar="Cydar"), name="") +
theme(legend.position = "top", legend.justification = c(1,1)) +
theme(axis.text.x = element_blank(), axis.ticks.x = element_blank(), axis.title.x = element_blank())
metric = "FDR"
pl_right <-
pl_df %>%
mutate(group=paste(method, design)) %>%
mutate(method=str_remove(method, "_batch")) %>%
ggplot(aes(as.factor(batchEffect), FDR, color =method)) +
geom_boxplot(outlier.alpha = 0) +
ggbeeswarm::geom_quasirandom(alpha=0.5, position="stack", size=0.5) +
facet_grid(.~design) +
xlab("Batch effect magnitude") +
theme_bw(base_size=16) +
geom_hline(yintercept = 0.1, linetype=2) +
# scale_color_manual(values = c(`~ condition`=method_colors["milo"], "black"))
scale_color_manual(values = method_colors, labels=c(milo="Milo", louvain="Louvain", cydar="Cydar"), name="") +
theme(legend.position = "top", legend.justification = c(1,1))
design_plot <-
(pl_left / pl_right) +
plot_layout(guides="collect") &
theme(legend.position = "top", legend.justification = c(1,1))
design_plot +
ggsave(paste0(figdir, "batchEffect_design.png"), height = 6, width = 10) +
ggsave(paste0(figdir, "batchEffect_design.pdf"), height = 6, width = 10, useDingbats=FALSE)
NA
NA
Visualize outcome in UMAP
colData(embryo_sce) <- read_csv(coldata_file) %>% column_to_rownames() %>% DataFrame()
[36m──[39m [1m[1mColumn specification[1m[22m [36m───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────[39m
cols(
.default = col_character(),
sample = [32mcol_double()[39m,
pool = [32mcol_double()[39m,
sequencing.batch = [32mcol_double()[39m,
doub.density = [32mcol_double()[39m,
doublet = [33mcol_logical()[39m,
cluster = [32mcol_double()[39m,
cluster.sub = [32mcol_double()[39m,
cluster.stage = [32mcol_double()[39m,
cluster.theiler = [32mcol_double()[39m,
stripped = [33mcol_logical()[39m,
sizeFactor = [32mcol_double()[39m,
Condition1_prob = [32mcol_double()[39m,
Condition2_prob = [32mcol_double()[39m
)
[36mℹ[39m Use [38;5;235m[48;5;253m[38;5;235m[48;5;253m`spec()`[48;5;253m[38;5;235m[49m[39m for the full column specifications.
Plot benchmark design
p1 <- umap_bath_df %>%
dplyr::rename(UMAP1=X1, UMAP2=X2) %>%
ggplot(aes(UMAP1, UMAP2)) +
geom_point_rast(size=0.1, raster.dpi = 500) +
theme_classic(base_size=16) +
guides(color=guide_colorbar(title.position="top", title.hjust = 0.5)) +
theme(axis.ticks = element_blank(),
axis.text = element_blank(),
legend.position = "top") +
xlab("UMAP1") + ylab("UMAP2") +
rasterize(geom_point(size=0.1, color="grey"), dpi = 300)
p2 <- umap_bath_df %>%
dplyr::rename(UMAP1=X1, UMAP2=X2) %>%
mutate(true=sce$Condition1_prob) %>%
mutate(true=ifelse(true < 0.5, 0.5, true)) %>%
arrange(true) %>%
ggplot(aes(UMAP1, UMAP2, color=true)) +
geom_point_rast(size=0.1, raster.dpi = 500) +
scale_color_viridis_c(name="C1 probability") +
theme_classic(base_size=14) +
guides(color=guide_colorbar(title.position="left", title.hjust = 1, title.vjust = 1, barwidth = 0.5, barheight = 3)) +
theme(axis.ticks = element_blank(),
axis.text = element_blank(),
legend.position = c(0.75,0.85), legend.background = element_blank()) +
xlab("UMAP1") + ylab("UMAP2")
rasterize(geom_point(size=0.1), dpi = 300)
geom_point: na.rm = FALSE
stat_identity: na.rm = FALSE
position_identity
p3 <- umap_bath_df %>%
dplyr::rename(UMAP1=X1, UMAP2=X2) %>%
mutate(true_labels=sce$synth_labels) %>%
ggplot(aes(UMAP1, UMAP2, color=true_labels)) +
geom_point_rast(size=0.1, raster.dpi = 500) +
scale_color_brewer(palette="Set1", labels=c(Condition1='C1', Condition2="C2"), name="") +
theme_classic(base_size=16) +
guides(color=guide_legend(override.aes = list(size=2))) +
theme(axis.ticks = element_blank(),
axis.text = element_blank(),
legend.position = c(0.85,0.95), legend.background = element_blank()) +
xlab("UMAP1") + ylab("UMAP2")
(p1 + p2 + p3)
Design matrix
Plot batch effect
library(ggrastr)
be_sce_ls <- lapply(c('0',"0.25", "0.5", "0.75", "1"), function(x) read_input_data(embryo_sce, indir, pop, enr, seed, x))
method="milo"
pop
## Plot condition probability
be_pl_ls <- lapply(be_sce_ls, function(sce) {
coldata_file <- list.files(indir, pattern=paste0(pop,".+", "enr",enr,".+",'seed', seed, ".coldata.csv"),
full.names = TRUE)
colData(sce) <- DataFrame(read_csv(coldata_file) %>% column_to_rownames())
data.frame(reducedDim(sce, "umap_batch")) %>%
rename(UMAP1=X1, UMAP2=X2) %>%
mutate(true=sce$Condition1_prob) %>%
mutate(true=ifelse(true < 0.5, 0.5, true)) %>%
arrange(true) %>%
ggplot(aes(UMAP1, UMAP2, color=true)) +
geom_point_rast(size=0.1, raster.dpi = 500) +
scale_color_viridis_c(name="C1 probability") +
theme_classic(base_size=14) +
guides(color=guide_colorbar(title.position="left", title.hjust = 1, title.vjust = 1, barwidth = 0.5, barheight = 3)) +
theme(axis.ticks = element_blank(),
axis.text = element_blank(),
legend.position = c(0.75,0.85), legend.background = element_blank()) +
xlab("UMAP1") + ylab("UMAP2")
}
)
## Plot batch
be_pl_ls2 <- lapply(be_sce_ls, function(sce) {
coldata_file <- list.files(indir, pattern=paste0(pop,".+", "enr",enr,".+",'seed', seed, ".coldata.csv"),
full.names = TRUE)
colData(sce) <- DataFrame(read_csv(coldata_file) %>% column_to_rownames())
data.frame(reducedDim(sce, "umap_batch")) %>%
rename(UMAP1=X1, UMAP2=X2) %>%
mutate(true=sce$synth_batches) %>%
ggplot(aes(UMAP1, UMAP2, color=true)) +
geom_point_rast(size=0.1, raster.dpi = 500) +
scale_color_viridis_d(name="Batch", option="cividis") +
theme_classic(base_size=18) +
guides(color=guide_legend(override.aes = list(size=2))) +
theme(axis.ticks = element_blank(),
axis.text = element_blank()) +
xlab("UMAP1") + ylab("UMAP2")
}
)
ptop <- wrap_plots(be_pl_ls, ncol=1, guides="collect") &
theme(legend.position = "right")
pbottom <- wrap_plots(be_pl_ls2, ncol=1, guides="collect")
(ptop | pbottom) +
plot_layout(guides="collect") +
ggsave(paste0(figdir, "batchEffect_UMAPs.pdf"), height=13, width = 8) +
ggsave(paste0(figdir, "batchEffect_UMAPs.png"), height=13, width = 8)
Design matrix w batch effect
m1 <- data.frame(colData(sce)[,c("synth_labels", "synth_samples", 'synth_batches')]) %>%
distinct(synth_labels,synth_samples) %>%
mutate(synth_labels=str_remove(synth_labels,"ondition"),
count=1) %>%
pivot_wider(id_cols = synth_samples, names_from=synth_labels, values_from=count,values_fill=0) %>%
pivot_longer(cols=c(C1, C2), names_to="synth_labels") %>%
ggplot(aes(synth_labels, synth_samples)) +
geom_tile(fill="white", color="black", size=1) +
geom_tile(data=. %>% filter(value>0), aes(fill=synth_labels), color="black", size=1) +
theme_classic(base_size=16) +
scale_fill_brewer(palette="Set1") +
guides(fill='none') +
xlab("Synthetic \ncondition") + ylab('Synthetic samples') +
theme(axis.text.y = element_blank(),axis.ticks.y = element_blank(),
axis.line = element_blank())
m2 <- data.frame(colData(sce)[,c("synth_labels", "synth_samples", 'synth_batches')]) %>%
distinct(synth_labels,synth_samples, synth_batches) %>%
mutate(synth_labels=str_remove(synth_labels,"ondition"),
count=1) %>%
pivot_wider(id_cols = synth_samples, names_from=synth_batches, values_from=count,values_fill=0) %>%
pivot_longer(cols=c(B1, B2), names_to="synth_batches") %>%
ggplot(aes(synth_batches, synth_samples)) +
geom_tile(fill="white", color="black", size=1) +
geom_tile(data=. %>% filter(value>0), aes(fill=synth_batches), color="black", size=1) +
theme_classic(base_size=16) +
scale_fill_viridis_d(option="cividis") +
guides(fill='none') +
xlab("Synthetic \nbatch") + ylab('Synthetic samples') +
theme(axis.text.y = element_blank(),axis.ticks.y = element_blank(), axis.title.y = element_blank(),
axis.line = element_blank())
(m1 + m2) +
# (p1 + p2 + p3) + des_pl +
plot_layout(widths=c(1,1), ncol=2) +
ggsave(paste0(figdir, "bm_design_batch.pdf"), height = 4, width = 4)
Load simulations with batch effects and correct with MNN
library(batchelor)
mnn_correct_batch_effect <- function(be_sce, k=50){
## Split in two SCE objects
b1_be_sce <- be_sce[,be_sce$synth_batches=="B1"]
b2_be_sce <- be_sce[,be_sce$synth_batches=="B2"]
be_mnn <- reducedMNN(reducedDim(b1_be_sce, "pca.corrected"), reducedDim(b2_be_sce, "pca.corrected"), k=k)
reducedDim(be_sce, "pca.MNN") <- be_mnn$corrected[colnames(be_sce),]
be_sce
}
## Simulate batch effects of different magnitude
save_corrected_be <- function(pop, pop_enr, seed, be_sd){
## Load coldata and PCA
outdir <- '/nfs/team205/ed6/data/milo_benchmark/synthetic_data/'
outprefix <- str_c("benchmark_embryo_pop_", pop, '_enr', pop_enr, "_seed", seed)
coldata <- read_csv(paste0(outdir, outprefix, ".coldata.csv")) %>% column_to_rownames()
X_pca <-read_csv(str_c(outdir, outprefix, "_batchEffect", be_sd, ".pca.csv")) %>% column_to_rownames()
## Add reduced dim + coldata to sce
colData(embryo_sce) <- DataFrame(coldata)
reducedDim(embryo_sce, "pca_batch") <- as.matrix(X_pca)
set.seed(seed)
sce_be <- mnn_correct_batch_effect(embryo_sce)
X_pca <- reducedDim(sce_be, "pca.MNN")
## Save reduced dims
write_csv(as.data.frame(X_pca) %>% rownames_to_column(), str_c(outdir, outprefix, "_batchEffect", be_sd,".MNNcorrected.pca.csv"))
}
be_sds <- unique(out_meta_df$batchEffect)
pops <- unique(out_meta_df$pop)
seeds=c(43)
for (pop in pops) {
for (seed in seeds) {
for (be_sd in c(0.5, 0.75, 1)) {
pop_enr = 0.8
save_corrected_be(pop, pop_enr, seed, be_sd)
}
}
}
Read all results (runned in wrapper submit_)
outdir <- "/nfs/team205/ed6/data/milo_benchmark/MNN_corrected/"
res_files <- list.files(outdir, pattern=".+DAresults.+.csv")
res_files_full <- list.files(outdir, pattern=".+DAresults.+.csv", full.names = TRUE)
# in_files <- list.files("~/data/milo_benchmark/synthetic_data/", pattern="_enr0.[78].+coldata.csv")
## Make data frame w benchmark parameters
mnn_out_meta_df <- data.frame(file_id = str_remove_all(res_files, "benchmark_embryo_pop_|.csv")) %>%
separate(col = file_id, sep = ".DAresults.", into=c("file_id", "method")) %>%
separate(col = file_id, sep = "_enr", into=c("pop", "file_id")) %>%
separate(col = file_id, sep = "_", into=c("enr", "seed", "batchEffect")) %>%
mutate(seed=str_remove(seed, "seed"), batchEffect=str_remove(batchEffect, "batchEffect"))
## Load results
mnn_outcome_df <- lapply(seq_along(res_files_full), function(i){
print(paste("Outcome no. ", i))
benchmark_df <- read_csv(res_files_full[i]) %>%
.outcome_by_prob(da_upper = embryo_thresh) %>%
mutate(DA_thresh=embryo_thresh) %>%
ungroup() %>%
dplyr::select(- method) %>%
bind_cols(mnn_out_meta_df[i,])
pop_enr <- as.numeric(mnn_out_meta_df[i,"enr"])
benchmark_df
}) %>%
purrr::reduce(bind_rows)
no_be <- outcome_df %>%
filter(batchEffect=="0") %>%
mutate(FDR = FP/(TP+FP))
uncorrected_be <- outcome_df %>%
filter(batchEffect %in% c("0.5", "0.75", '1')) %>%
mutate(FDR = FP/(TP+FP))
pl_df <- mnn_outcome_df %>%
filter(enr > 0.6) %>%
mutate(batchEffect = str_remove(batchEffect, ".MNNcorrected")) %>%
mutate(FDR = FP/(TP+FP)) %>%
mutate(TPR=ifelse(is.nan(TPR), 0, TPR),
FPR=ifelse(is.nan(FPR), 0, FPR),
FDR=ifelse(is.nan(FDR), 0, FDR),
Precision=ifelse(is.nan(Precision), 0, Precision)) %>%
mutate(pop=str_replace(pop, "_", " ")) %>%
# mutate(pop_size=pop_sizes[pop]) %>%
# arrange(pop_size) %>%
mutate(pop=factor(pop, levels=unique(pop))) %>%
mutate(seed=as.numeric(seed), enr=as.numeric(enr), batchEffect=as.numeric(batchEffect))
pl_top <- bind_rows(mutate(no_be, class="no Batch Effect"),
mutate(uncorrected_be, class="Uncorrected"),
mutate(pl_df, class="MNN corrected")) %>%
mutate(class=factor(class, levels=c("no Batch Effect", "MNN corrected", "Uncorrected"))) %>%
mutate(FDR = FP/(TP+FP)) %>%
mutate(TPR=ifelse(is.nan(TPR), 0, TPR),
FPR=ifelse(is.nan(FPR), 0, FPR),
FDR=ifelse(is.nan(FDR), 0, FDR),
Precision=ifelse(is.nan(Precision), 0, Precision)) %>%
filter(method != "milo_batch" & method !="louvain_batch" & method !="cydar_batch") %>%
ggplot(aes(as.factor(batchEffect), color=method, TPR)) +
geom_boxplot(outlier.size = 0.5) +
facet_grid(.~class, space="free", scales="free") +
scale_color_methods() +
scale_fill_methods() +
theme_bw(base_size=16) +
xlab("Batch effect magnitude") +
theme(axis.text.x = element_blank(), axis.ticks.x = element_blank(), axis.title.x = element_blank())
pl_bottom <- bind_rows(mutate(no_be, class="no Batch Effect"),
mutate(uncorrected_be, class="Uncorrected"),
mutate(pl_df, class="MNN corrected")) %>%
mutate(class=factor(class, levels=c("no Batch Effect", "MNN corrected", "Uncorrected"))) %>%
mutate(FDR = FP/(TP+FP)) %>%
mutate(TPR=ifelse(is.nan(TPR), 0, TPR),
FPR=ifelse(is.nan(FPR), 0, FPR),
FDR=ifelse(is.nan(FDR), 0, FDR),
Precision=ifelse(is.nan(Precision), 0, Precision)) %>%
filter(method != "milo_batch" & method !="louvain_batch" & method !="cydar_batch") %>%
ggplot(aes(as.factor(batchEffect), color=method, FDR)) +
geom_boxplot(outlier.size = 0.5) +
facet_grid(.~class, space="free", scales="free") +
scale_color_methods() +
scale_fill_methods() +
theme_bw(base_size=16) +
xlab("Batch effect magnitude")
mnn_plot <- (pl_top / pl_bottom +
plot_layout(guides="collect") &
theme(legend.position="top")) +
ggsave(paste0("~/mount/gdrive/milo/Figures/resubmission2/supplementary/suppl_fig_bm_MNN.pdf"), height = 6, width = 8)
mnn_plot
(mnn_plot & theme(legend.position = "top")) +
# ggsave(paste0(figdir, "batchEffect_MNNcorrected.png"), height = 6, width = 10) +
# ggsave(paste0(figdir, "batchEffect_MNNcorrected.pdf"), height = 6, width = 10)
ggsave("~/mount/gdrive/milo/Figures/resubmission/supplementary/suppl_fig_bm_MNN.pdf", height = 6, width = 10)
Plot UMAP
X_pca_mnn <- read_csv("/nfs/team205/ed6/data/milo_benchmark/synthetic_data/benchmark_embryo_pop_Somitic_mesoderm_enr0.8_seed43_batchEffect0.75.MNNcorrected.pca.csv") %>%
column_to_rownames()
all(rownames(X_pca_mnn) == colnames(embryo_sce))
coldata <- read_csv("/nfs/team205/ed6/data/milo_benchmark/synthetic_data/benchmark_embryo_pop_Somitic_mesoderm_enr0.8_seed43.coldata.csv")
colData(embryo_sce) <- coldata %>% column_to_rownames() %>% DataFrame()
reducedDim(embryo_sce, "pca_batch") <- as.matrix(X_pca_mnn)
embryo_sce <- runUMAP(embryo_sce, dimred="pca_batch", name="umap_batch")
indir <- "~/data/milo_benchmark/synthetic_data/"
res <- read_csv("/nfs/team205/ed6/data/milo_benchmark/benchmark_embryo_pop_Somitic_mesoderm_enr0.8_seed43_batchEffect0.75.DAresults.milo.csv")
embryo_sce$pred <- res$pred
embryo_sce$true <- res$true
plotReducedDim(embryo_sce, "umap_batch", colour_by="Condition1_prob", point_size=0.1)
plotReducedDim(embryo_sce, "umap_batch", colour_by="pred", point_size=0.1)
plotReducedDim(embryo_sce, "umap_batch", colour_by="true", point_size=0.1)
res %>%
.outcome_by_prob(da_upper = 0.6) %>%
mutate(FDR = FP/(TP+FP))
Show why Milo has TPR=0 if batch covariate not included.
data_id="embryo"
pop="Gut"
pop_enr="0.8"
seed='43'
## Load coldata and PCA
outdir <- '/nfs/team205/ed6/data/milo_benchmark/synthetic_data/'
outprefix <- str_c("benchmark_", data_id, "_pop_", pop, '_enr', pop_enr, "_seed", seed)
coldata <- read_csv(paste0(outdir, outprefix, ".coldata.csv")) %>% column_to_rownames()
X_pca <-read_csv(str_c(outdir, str_remove(outprefix, "_capped_logit.."), "_batchEffect", be_sd, ".pca.csv")) %>% column_to_rownames()
## Find DA probability x cell
k=50
bm_params = list(
milo = list(k=k)
)
## Add reduced dim + coldata to sce
colData(embryo_sce) <- DataFrame(coldata)
reducedDim(embryo_sce, "pca_batch") <- as.matrix(X_pca)
## Run milo
milo_res <- run_milo(embryo_sce, condition_col="synth_labels", sample_col='synth_samples',
reduced.dim = "pca_batch", d=30, k=bm_params$milo$k)
design_df <- as.tibble(colData(embryo_sce)[c('synth_samples', "synth_labels")]) %>%
distinct() %>%
column_to_rownames('synth_samples')
plotNhoodMA(milo_res$DAres)
ggplot(milo_res$DAres, aes(PValue)) + geom_histogram()
out <- milo2output(milo_res$Milo, milo_res$DAres, out_type = out_type)
head(nhoodCounts(milo_res$Milo)[,design_df$synth_labels=="Condition1"])
add_batch_effect_nonlinear <- function(sce, batch_col="synth_batches", theta_deg=20, dims=1:2){
## Simulate rotation of first 2 PCs
theta=theta_deg*pi/180
rotM=matrix(0,nrow=2,ncol=2)
rotM[1,]=c(cos(theta),-sin(theta))
rotM[2,]=c(sin(theta),cos(theta))
cellids_sample <- split(sce$cell, sce[[batch_col]])
X_pca <- reducedDim(sce, "pca.corrected")
X_pca_batch <- X_pca
## Apply rotation to one of the batches
X_pca_batch[cellids_sample[[names(cellids_sample)[1]]],dims] <- t(rotM %*% t(X_pca_batch[cellids_sample[[names(cellids_sample)[1]]],dims]))
reducedDim(sce, "pca_batch") <- X_pca_batch
sce
}
coldata_file <- list.files(indir, pattern=paste0(pop,".+", "enr",enr,".+",'seed', seed, ".coldata.csv"),
full.names = TRUE)
colData(embryo_sce) <- read_csv(coldata_file) %>% column_to_rownames() %>% DataFrame()
batch_col="synth_batches"
embryo_sce <- add_batch_effect_nonlinear(embryo_sce, dims=c(3,5), theta_deg = 30)
embryo_sce <- runUMAP(embryo_sce, dimred="pca_batch", name = 'umap_batch', n_dimred=1:30)
data.frame(reducedDim(embryo_sce, "umap_batch")) %>%
rename(UMAP1=X1, UMAP2=X2) %>%
mutate(true=embryo_sce$synth_batches) %>%
ggplot(aes(UMAP1, UMAP2, color=true)) +
geom_point(size=0.1) +
scale_color_viridis_d(name="Batch", option="cividis") +
theme_classic(base_size=18) +
guides(color=guide_legend(override.aes = list(size=2))) +
theme(axis.ticks = element_blank(),
axis.text = element_blank()) +
xlab("UMAP1") + ylab("UMAP2")
data.frame(reducedDim(embryo_sce, "UMAP")) %>%
rename(UMAP1=X1, UMAP2=X2) %>%
mutate(true=embryo_sce$synth_batches) %>%
ggplot(aes(UMAP1, UMAP2, color=true)) +
geom_point(size=0.1) +
scale_color_viridis_d(name="Batch", option="cividis") +
theme_classic(base_size=18) +
guides(color=guide_legend(override.aes = list(size=2))) +
theme(axis.ticks = element_blank(),
axis.text = element_blank()) +
xlab("UMAP1") + ylab("UMAP2")
# be_sce_ls <- lapply(c('0',"0.25", "0.5", "0.75", "1"), function(x) read_input_data(embryo_sce, indir, pop, enr, seed, x, run_umap = FALSE))
Make non-linear batch effect for all populations
## Simulate batch effects of different magnitude
save_nonlinear_be <- function(sce, pop, pop_enr, seed){
## Load coldata and PCA
outdir <- '/nfs/team205/ed6/data/milo_benchmark/synthetic_data/'
outprefix <- str_c("benchmark_embryo_pop_", pop, '_enr', pop_enr, "_seed", seed)
coldata <- read_csv(paste0(outdir, outprefix, ".coldata.csv")) %>% column_to_rownames()
## Add reduced dim + coldata to sce
colData(sce) <- DataFrame(coldata)
set.seed(seed)
sce_be <- add_batch_effect_nonlinear(embryo_sce, dims=c(3,5), theta_deg = 30)
X_pca <- reducedDim(sce_be, "pca_batch")
## Save reduced dims
write_csv(as.data.frame(X_pca) %>% rownames_to_column(), str_c(outdir, outprefix, "_batchEffectNonLinear30.pca.csv"))
}
pops <- unique(out_meta_df$pop)
pop_enrs <- unique(out_meta_df$enr)
seeds <- unique(out_meta_df$seed)
for (pop in pops) {
for (pop_enr in pop_enrs[1:3]) {
for (seed in seeds) {
save_nonlinear_be(embryo_sce, pop, pop_enr, seed)
}
}
}
Running in run_DA_nonlinear.R.
Read all results
outdir <- "/nfs/team205/ed6/data/milo_benchmark/"
res_files <- list.files(outdir, pattern="NonLinear.+DAresults.+.csv")
res_files_full <- list.files(outdir, pattern="NonLinear.+DAresults.+.csv", full.names = TRUE)
## Make data frame w benchmark parameters
nonl_out_meta_df <- data.frame(file_id = str_remove_all(res_files, "benchmark_embryo_pop_|.csv")) %>%
separate(col = file_id, sep = ".DAresults.", into=c("file_id", "method")) %>%
separate(col = file_id, sep = "_enr", into=c("pop", "file_id")) %>%
separate(col = file_id, sep = "_", into=c("enr", "seed", "batchEffect")) %>%
mutate(seed=str_remove(seed, "seed"), batchEffect=str_remove(batchEffect, "batchEffect"))
## Load results
nonl_outcome_df <- lapply(seq_along(res_files_full), function(i){
print(paste("Outcome no. ", i))
benchmark_df <- read_csv(res_files_full[i]) %>%
.outcome_by_prob(da_upper = 0.6) %>%
mutate(DA_thresh=0.6) %>%
ungroup() %>%
dplyr::select(- method) %>%
bind_cols(nonl_out_meta_df[i,])
pop_enr <- as.numeric(nonl_out_meta_df[i,"enr"])
benchmark_df
}) %>%
purrr::reduce(bind_rows)
nonl_outcome_df
pl_df <- nonl_outcome_df %>%
filter(enr > 0.6) %>%
mutate(FDR = FP/(TP+FP)) %>%
mutate(TPR=ifelse(is.nan(TPR), 0, TPR),
FPR=ifelse(is.nan(FPR), 0, FPR),
FDR=ifelse(is.nan(FDR), 0, FDR),
Precision=ifelse(is.nan(Precision), 0, Precision)) %>%
mutate(pop=str_replace(pop, "_", " "))
pl_df %>%
ggplot(aes(pop, TPR)) +
ggbeeswarm::geom_quasirandom(alpha=0.5) +
geom_hline(yintercept = 0.8, linetype=2) +
theme_bw(base_size = 16) +
scale_color_brewer(palette="Dark2") +
facet_grid(enr~., labeller = enr_labeller) +
pl_df %>%
ggplot(aes(pop, FDR)) +
ggbeeswarm::geom_quasirandom(alpha=0.5) +
geom_hline(yintercept = 0.1, linetype=2) +
theme_bw(base_size = 16) +
scale_color_brewer(palette="Dark2") +
facet_grid(enr~., labeller = enr_labeller) +
plot_layout(guides='collect')
lin_be <- outcome_df %>%
filter(method=="milo_batch" & enr %in% c(0.7, 0.8) & DA_thresh==0.6)
bind_rows(
mutate(lin_be, class="Linear batch effect"),
mutate(nonl_outcome_df, class="Non Linear\n batch effect") %>%
filter(enr > 0.6) %>%
mutate(enr=as.numeric(enr), seed=as.numeric(seed), batchEffect=as.numeric(str_remove(batchEffect, "NonLinear")))
) %>%
ggplot(aes(as.factor(batchEffect), TPR, color=method)) +
geom_boxplot() +
ggbeeswarm::geom_quasirandom(alpha=0.5) +
facet_grid(enr~class, scales="free", space="free") +
scale_color_manual(values=method_colors[[4]], labels=setNames(method_labels, method_names)) +
theme_bw(base_size=16) +
xlab("Batch effect magnitude")
plotUMAP(embryo_sce, colour_by="Condition1_prob")
Subcluster all celltype populations (there is a caveat here that I am not recalculating the PCA space for all subsets, but it should bring home the message regardless)
embryo_sce$subcluster <- NA
k=15
for (pop in unique(embryo_sce$celltype)) {
pop_sce <- embryo_sce[,embryo_sce$celltype==pop]
X_red_dim <- reducedDim(pop_sce, "pca.corrected")
sce.graph <- buildKNNGraph(t(X_red_dim), k=k)
louvain.clust <- cluster_louvain(sce.graph)
louvain.clust.ids <- membership(louvain.clust)
pop_sce$subcluster <- paste(pop, as.character(louvain.clust.ids), sep="_")
subclusters <- setNames(pop_sce$subcluster, colnames(pop_sce))
colData(embryo_sce)["subcluster"][names(subclusters),] <- subclusters
}
# pop_sce <- runUMAP(pop_sce, dimred="pca.corrected")
subclusters_umap <- data.frame(reducedDim(embryo_sce, "UMAP")) %>%
mutate(subcluster=embryo_sce$subcluster) %>%
mutate(subcluster=factor(subcluster, levels=sample(unique(subcluster)))) %>%
ggplot(aes(X1, X2, color=subcluster)) +
geom_point(size=0.1) +
guides(color="none") +
xlab("UMAP1") + ylab("UMAP2") +
theme_classic(base_size=18)
Make simulated labels
embryo_sce <- add_synthetic_labels_pop(embryo_sce, pop="Somitic mesoderm", pop_column = "celltype", seed=42, pop_enr=0.8)
true_labels <- ifelse(embryo_sce$Condition2_prob < 0.4, "NegLFC", ifelse(embryo_sce$Condition2_prob > 0.6, "PosLFC", "NotDA"))
colData(embryo_sce)[["true_labels"]] <- true_labels
Testing for DA with GLM on subclusters
condition_col = "synth_labels"
sample_col = "synth_samples"
sce <- embryo_sce
## Make design matrix
design_df <- as.tibble(colData(sce)[c(sample_col, condition_col)]) %>%
distinct() %>%
rename(sample=sample_col)
design <- formula(paste('Freq ~', condition_col, "+ offset(log(N_s))", collapse = ' '))
## Test DA in subclusters
condition_vec <- colData(embryo_sce)[[condition_col]]
sample_labels <- colData(embryo_sce)[[sample_col]]
clust.df <- data.frame("cell_id"=colnames(embryo_sce), "Louvain.Clust"=embryo_sce$subcluster)
clust.df$Sample <- sample_labels
clust.df$Condition <- condition_vec
louvain.count <- table(clust.df$Louvain.Clust, clust.df$Sample)
attributes(louvain.count)$class <- "matrix"
df <- melt(louvain.count, varnames=c("cluster", "sample"), value.name="Freq") %>%
mutate(cluster=factor(cluster)) %>%
left_join(design_df, by="sample") %>%
group_by(sample) %>%
mutate(N_s=sum(Freq)) %>%
ungroup() %>%
group_by(cluster) %>%
do(model=glm(design, data=., family="poisson"))
res_df <- t(sapply(df$model, function(x) summary(x)$coefficients[nrow(summary(x)$coefficients),]))
colnames(res_df) <- c("logFC","Std. Error", "z value", "Pval" )
louvain.res <- cbind(df, res_df) %>%
mutate(FDR=p.adjust(Pval, method = "BH"))
rownames(louvain.res) <- louvain.res$cluster
clust.df$logFC <- louvain.res[clust.df$Louvain.Clust, 'logFC']
clust.df$FDR <- louvain.res[clust.df$Louvain.Clust, 'FDR']
embryo_sce$predDA_subclusters <- louvain2output(clust.df, out_type = "labels")
clust.df %>%
ggplot(aes(logFC, -log10(FDR))) + geom_point()
## Test DA in cell type clusters
clust.df <- data.frame("cell_id"=colnames(embryo_sce), "Louvain.Clust"=embryo_sce$celltype)
clust.df$Sample <- sample_labels
clust.df$Condition <- condition_vec
louvain.count <- table(clust.df$Louvain.Clust, clust.df$Sample)
attributes(louvain.count)$class <- "matrix"
df <- melt(louvain.count, varnames=c("cluster", "sample"), value.name="Freq") %>%
mutate(cluster=factor(cluster)) %>%
left_join(design_df, by="sample") %>%
group_by(sample) %>%
mutate(N_s=sum(Freq)) %>%
ungroup() %>%
group_by(cluster) %>%
do(model=glm(design, data=., family="poisson"))
res_df <- t(sapply(df$model, function(x) summary(x)$coefficients[nrow(summary(x)$coefficients),]))
colnames(res_df) <- c("logFC","Std. Error", "z value", "Pval" )
louvain.res <- cbind(df, res_df) %>%
mutate(FDR=p.adjust(Pval, method = "BH"))
rownames(louvain.res) <- louvain.res$cluster
clust.df$logFC <- louvain.res[clust.df$Louvain.Clust, 'logFC']
clust.df$FDR <- louvain.res[clust.df$Louvain.Clust, 'FDR']
embryo_sce$predDA_celltype <- louvain2output(clust.df, out_type = "labels")
clust.df %>%
ggplot(aes(logFC, -log10(FDR))) + geom_point()
milo_res <- run_milo(embryo_sce, condition_col="synth_labels", sample_col="synth_samples", reduced.dim = "pca.corrected",
k=50, d = 30)
embryo_sce$predDA_milo <- milo2output(milo_res$Milo, milo_res$DAres, out_type = "labels", alpha = 0.1)
# embryo_sce$predDA <- louvain2output(clust.df, out_type = "labels")
pl_df <- data.frame(reducedDim(embryo_sce, "UMAP")) %>%
mutate(subcluster=embryo_sce$subcluster) %>%
mutate(subcluster=factor(subcluster, levels=sample(unique(subcluster)))) %>%
mutate(predDA_subclusters=embryo_sce$predDA_subclusters,
predDA_celltype=embryo_sce$predDA_celltype,
predDA_milo=embryo_sce$predDA_milo,
trueDA = embryo_sce$true_labels)
true_pl <- pl_df %>%
ggplot(aes(X1, X2, color=trueDA)) +
geom_point(size=0.1) +
xlab("UMAP1") + ylab("UMAP2") +
theme_classic(base_size=18) +
scale_color_manual(values=c(NotDA="grey", PosLFC="Red", NegLFC="Blue"),name="") +
guides(color="none") +
ggtitle("True DA")
subcl_plot <- pl_df %>%
ggplot(aes(X1, X2, color=predDA_subclusters)) +
geom_point(size=0.1) +
xlab("UMAP1") + ylab("UMAP2") +
theme_classic(base_size=18) +
scale_color_manual(values=c(NotDA="grey", PosLFC="Red", NegLFC="Blue"),name="") +
guides(color=guide_legend(override.aes = c(size=2))) +
ggtitle("GLM on subclusters")
cl_plot <- pl_df %>%
ggplot(aes(X1, X2, color=predDA_celltype)) +
geom_point(size=0.1) +
xlab("UMAP1") + ylab("UMAP2") +
theme_classic(base_size=18) +
scale_color_manual(values=c(NotDA="grey", PosLFC="Red", NegLFC="Blue"),name="") +
guides(color="none") +
ggtitle("GLM on clusters")
milo_pl <- pl_df %>%
ggplot(aes(X1, X2, color=predDA_milo)) +
geom_point(size=0.1) +
xlab("UMAP1") + ylab("UMAP2") +
theme_classic(base_size=18) +
scale_color_manual(values=c(NotDA="grey", PosLFC="Red", NegLFC="Blue"), name="") +
guides(color="none") +
ggtitle("Milo")
fig2 <- true_pl + milo_pl + cl_plot + subcl_plot +
plot_layout(ncol=2, nrow=2, guides="collect")
Compare size of subclusters and size of neighbourhoods
size_fig <- (data.frame(table(embryo_sce$subcluster)) %>%
ggplot(aes(Freq)) + geom_histogram() +
theme_classic(base_size = 16) +
annotate("text", label=paste0("N = ", length(unique(embryo_sce$subcluster))), x=750, y=20, size=5) +
xlab("Subcluster size") +
xlim(0, 1000)) /
(plotNhoodSizeHist(milo_res$Milo) +
xlim(0, 1000) +
annotate("text", label=paste0("N = ", ncol(nhoods(milo_res$Milo))), x=750, y=600, size=5) +
xlab("Milo neighbourhood size"))
size_fig
((((subclusters_umap + ggtitle("Subclusters")) / size_fig) + plot_layout(ncol=1)) |
fig2 ) +
plot_layout(ncol=2, widths=c(1,2)) +
plot_annotation(tag_levels = 'A') +
ggsave("~/mount/gdrive/milo/Figures/RebuttalFig1_microclusters.png", width = 14, height = 8)